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Latest Thesis and Research Topics in Software Engineering

List Software Engineering Research Topics

If you ask an experienced dissertation writer that what is the hardest part of writing a dissertation, there is a high probability that their answer will be, finding the right dissertation topic. This is because a dissertation topic paves the way for your dissertation’s journey. A good topic mean a good journey and a bad topic means a stressful and bad journey. Therefore, it is immensely important that you give the utmost attention to your dissertation topic.

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List of Free Software Engineering Dissertation Topics and Titles

To make sure that your journey goes as smooth and hinderance free as possible, our team of the most prolific academic writers have prepared a list of the best free custom software engineering dissertation topics and software engineering dissertation ideas that you can find online.

1.1 Research Objective

  • To evaluate the importance of the information provided on the social media platforms like Facebook, Instagram, twitter, etc.
  • To determine the actions of the customers after viewing the social media regarding a product or service.
  • To examine the elements which enforces the individual to follow the social media.
  • To understand the basis on which the consumers take decision.
  • To analyse the impact of the use of social media
  • To understand the impacts of trends going on in the social media.
  • To determine the reasons behind the turning away of consumers from traditional media sources (Newspapers, T.V).
  • Analysing the significance of social media in the customers decision making.

1.2 Research Aims

The aim of the current topic, Impact of Social Media on the Purchase Decision is about having the complete understanding of the significance that people give to the social media which effects their decision of buying. The aim is to highlight the forces which are present to impact the decision. This will also find out how the influence of social media provides access to a huge information.

Aims The aim of this study is that evaluation of the system integration that enabled the rapid advancement of technology from industrial aged system to the information-based models. However, technology advancement in different areas for the building of devices make sufficient that was not possible even some years before. The number of technologies altered ways in which networks were built. The information-based models are a type of data application model which is used in the data warehouses. Therefore, the aim of this study is that the role of the system integration which enabled the rapid advancement of the technology from the industrial aged system to the information-based models. Objectives The objectives of this study are the following:

  • To evaluate the system integration in the advancement of technology.
  • To analyse the rapid advancement of technology from the industrial age.
  • To analyse the rapid advancement of the technology from the industrial age to the information-based models.

Aims This study aims to determine the modelling patterns in software design. And this study based on the understanding of the software patterns which provide solutions to recurring the design problems. Software pattern widely used in the development of the projects from small scale to the large scale and this study provides the innovative solution to recurring the design problems. In this study, discuss the specific patterns which illustrate the consequences on the specific quality of the selected system. The software’s patterns inherited the specific quality which influences both negatively and positively by patterns that used in the system. Objectives The objectives of this study are the following:

  • To analyse the different modelling patterns in software designing.
  • To analyse and understand the different software patterns.
  • To understand the problems of design pattern in software designing.
  • To understand the software patterns which provide the solution to recurring design problems.

Microsoft .NET frameworks have been widely used by various organizations in order to build room scheduling systems as well as work mapping systems. This case study aims to highlight the developmental process of room scheduling system using the Microsoft .NET frameworks for the purposeful use in various industries. Moreover, the study aims to shed light on the significance of room scheduling as well as work mapping systems in organizational purposes. Furthermore, it is the aim of the current study to investigate the developmental process of work mapping system using the software framework of Microsoft .NET.

Objectives:

Following are the objectives of the current study presented by the researcher:

  • To explore the concept of room scheduling by using a software framework while shedding light on the Microsoft .NET framework.
  • To understand the work mapping system of the Microsoft .NET frameworks.
  • To identify the significance of using Microsoft .NET frameworks for developing the room scheduling and work mapping system to be used in organizations.
  • To analyse the impact of using room scheduling and work mapping systems in an organization developed using the Microsoft frameworks.
  • To evaluate the development process of room scheduling and work mapping system using the Microsoft framework.

User documentation software has been effective in the effort to translate a language as well as make it understand better for the user. The current study aims to investigate the significance of using the software user documentation system in facilitating with the comprehensibility and translatability of languages. Furthermore, the researcher aims to analyse the disadvantages involved with using this system and determine these in contrast to the advantages involved. Moreover, it is the aim of the current research to identify the processes involved in the development and utilization of software user documentation.

  • To determine the significant uses of software user documentation system regarding the language translation in the light of various industries.
  • To identify the various processes involved in the software user documentation with respect to the function of language translation and comprehensibility.
  • To investigate the impact of utilizing software user documentation for the purpose of language comprehension and translation.
  • To state the disadvantages in contrast to the advantages of using the software user documentation system in an effort to facilitate comprehensibility and translatability of languages.

Most of the interaction with software is done using a graphic user interface (GUI). However, the testing of the graphic user interface has been neglected until recently. The existing technology for testing a Graphic user interface has been extremely resource-intensive. The current research proposes to investigate the cost-effective model-based techniques for the Graphic user interface (GUI) testing. For this purpose, the researcher aims to understand the effectiveness of these techniques as well as identify the best possible technique with respect to all the aspects involved like cost-effectiveness and efficiency. Furthermore, it is the aim of the research to understand the cost-effective model-based techniques that are utilized for the testing of Graphic user interface.

  • To identify the various techniques used for the testing of Graphic user interface (GUI).
  • To investigate the effectiveness of these graphic user interface testing techniques.
  • To determine the factors that make a model-based graphic user interface testing technique cost-effective as well as efficient.
  • To understand the cost-effective model-based techniques for the testing of a graphic user interface with respect to the aspect of cost-effectiveness.
  • To identify the different cost-effective model-based techniques used for graphic user interface testing.

It is crucial to test a software system to check and maintain functional effectiveness. Moreover, the testing of early detection of faults and errors of the software system especially that are safety crucial is extremely necessary or they could result in the death or a serious injury of a person. The research has been scarce in testing the effectiveness of existing technology for testing a Graphic user interface. For this reason, the current research proposes to investigate the effectiveness of model-based techniques for the Graphic user interface (GUI) testing. The current study aims to highlight the subject of model-based testing techniques for the purpose of software system testing.

  • To investigate the significance of early fault detection of a software system and the advantages it possesses.
  • To identify the various model-based testing techniques that can be used for the early fault detection on software systems.
  • To highlight the uses of model-based software testing techniques.
  • To evaluate the factors involved in the early detection of software malfunction using model-based testing techniques.

To explore the factors that make a model-based technique for software testing effective.

It is essential for the software developers and managers to know about different aspects of their systems. For the maintainability of software, different quality assessment software has been invented. In this investigative study, the researcher aims to highlight the impact of the Software Quality Assessment based on Lifecycle Expectations (SQALE) method along with exploring its usability. Moreover, it is the aim of the current study to identify the different methods of software quality assessment used to measure the quality of Java and C# programming languages.

  • To understand the Lifecycle expectation SQALE method.
  • To explore the usability of Software Quality Assessment by utilizing Lifecycle Expectations (SQALE) method.
  • To analyse the different existing ways for measuring the quality of Java and C# programming source code.
  • To identify the factors associated with the software quality assurance for measuring the quality of the project.
  • To explore the different programming languages for estimating the maintainability of the source code used in the complex projects.
  • To analyse the usability of the Software Quality Assessment based on Lifecycle Expectations (SQALE) method to measure the quality of Java and C# source code with respect to the info Support organization.

The use of agile environment methods in the mainstream software development community has been becoming widely popular. Although, there have been various academic researches in educational settings regarding the subject of agile environment process. However, the research regarding the usage of agile environment methodologies with reference to the speedy delivery of high-quality software is scarce. Due to this fact, the researcher of the current study aims to explore the usability of an agile environment by the project operations team for the purpose of speedy delivery of high-quality software. Moreover, it is the aim of the current study to investigate the perception of the project operations team regarding the agile development process as well.

  • To understand the methodologies of an agile environment with respect to the project management team.
  • To investigate the impact of using an agile environment methodologies by the project operations regarding the speedy delivery of high-quality software.
  • To explore the perceptions of the project management team regarding the agile development methodologies with context to the speedy delivery of high-quality software.
  • To evaluate the effectiveness of agile environment methodologies in providing with the speedy delivery of high-quality software.

It has been greatly observed through research that software planning is the process which if done effectively can reflect the project success in later stages. The current study aims to investigate the causal relationship between the project planning process with project success. For this purpose, the researcher aims to identify the factors associated with project success. Moreover, it is the aim of the current study to evaluate the aspects that are involved in the project planning method which lead to the successful execution as well as the success of a project. Furthermore, it is the aim of this research study to explore the process of software project planning as well.

  • To understand the process of software planning with respect to the related aspects involved.
  • To investigate the factors involved in determining the success of the project due to the initial stages of project planning.
  • To identify the processes involved in assessing project success.
  • To analyse the significance that project planning holds in determining the success of a project.
  • To investigate the association of the causal relationship between project planning and project success.
  • To evaluate the factors which are involved in the project planning method that leads to the effective association and success of a project.

It has been stressed upon by various researchers within the software engineering community that the visualization of statistical content is essential. Several studies have been conducted regarding this subject however, there is a need for identifying and evaluating the existing visualization techniques. For this reason, it is the aim of the researcher to investigate the various visualization techniques that can be used for the visualization of software metric. Moreover, it is the aim of the current study to analyse the significance of using visualization techniques for the purpose of visualization of software metrics. Furthermore, the study aims to investigate the different viewpoints of several studies regarding the subject of discussion.

  • To identify the difficulties encountered with respect to the software metrics in context to not being visualized.
  • To analyse the significance of visualizing of the software metrics.
  • To determine the various visualization techniques currently existing that can be utilized for the visualization of the statistical content involved in software metrics.

To investigate the effectiveness of the visualization techniques with reference to their visualization of the statistical content of software metrics.

Using a groupware tool for making improvements in the software process has become a widespread practice along with software engineers. The current study aims to investigate the process of software development with respect to all the aspects involved in the process. The researcher aims to highlight the subject of using a groupware tool for the improvement of the software process. Moreover, the process of software development has become a cooperative rather than individual work. Hence, it is the aim of the current study to determine the advantages and disadvantages of the cooperative software development process. Furthermore, it is the aim of the researcher to analyse the supporting distributed cooperation in software development.

  • To explore the use of groupware tool for the purpose of software process improvement.
  • To explore the process of software development while also shedding light on the improvement assessing techniques.
  • To identify the significance of using a groupware tool for the purpose of developing and improving the software process.
  • To analyse the advantages as well as the disadvantages of distributed cooperation in software development.
  • To determine the impact of distributed cooperation in software development process regarding the aspect of effective development.

In the current study, the researcher aims to shed light on the topic of software prototypes with context to the best results provided by them regarding the ontology enabled traceability mechanisms. It is the aim of the researcher to identify the different existing prototypes that are used for the purpose of ontology enabled traceability. The significance of the ontology enabled traceability mechanisms is also discussed in this research. Moreover, the aim of the research includes comparing various prototypes with respect to the best results in ontology enabled traceability mechanisms.

Following are the objectives of the current research study presented by the researcher:

  • To identify the different existing software prototypes that can be used for the ontology enables traceability mechanisms.
  • To evaluate the significance of ontology enabled traceability mechanisms.
  • To analyse the factors involved in determining the best results in ontology enabled mechanisms.
  • To determine the factors that are associated with the software prototypes with respect to the best results achieved in ontology enabled traceability mechanisms.
  • To compare the different software prototypes in context to the ontology enabled traceability mechanisms.

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Software Engineering Research Ideas For Marvellous Dissertations

You thought we were done with just a few software engineering dissertation topics? Not at all, our writers have also produced a list of the best free software engineering dissertation ideas that you can use to custom make software engineering dissertation topics according to your needs and convenience.

Aims This study aims to understand the hierarchical approach to software testing. The other aim of this is that software quality assurance analyst will make sure that the software is must be without any bugs. However, for the development of the system with high quality of software testing is important for the software analyst which must make sure that software is free from any bugs and viruses. The validation and verification activities are conducted to enhance the quality of software throughout the lifecycle of software development. Objectives The objectives of this study are briefly described below.

  • To understand the selection method of the software testing techniques with the use of the analytic hierarchy process.
  • To analyse the role of SQA analyst in software testing.
  • To understand and make sure that software is must be free from the bugs.
  • To observe the significance of the right hierarchical approach for software testing.

Aims This study aims to evaluate and analyse the work process of a web content management system. This study is based on the case study of the Facebook store. The web content management system provides an optimal solution by the information organisation, managing and creating the enterprise knowledge. This study aims to show the case study of the Facebook store with information management products which are also called the content management system. This is the consists of the work process in which content management products have been compared, analysed and evaluated with the special table which created to point the actual functionalities of products which offered on market. Objectives The objectives of this study are the following:

  • To analyse the content management system.
  • To evaluate for analysing the work process of the web content management system.
  • To analyse the Facebook store company satisfaction which is related to information management and knowledge.

Aims The aim of this study is that it is based on the exploratory study on understanding the effectiveness of fault tolerance analysis of sorting networks. This study also aims that it is the general technique for enhancing the reliability of the sorting networks and the other networks which are comparator based are presented. This technique is also sufficient because it converts the unreliable comparators to the fault-tolerant network which produces the correct output with the probability. Therefore, this study based on the fault analysis to sort out the networks. This study analyses the fault-tolerant mapping by a technique combining routing and mapping, with remapping based techniques and redundancy based techniques. Objectives The objectives of this study are the following:

  • To determine the fault tolerance analysis.
  • To evaluate the effectiveness of the fault tolerance analysis.
  • To assess the understanding of the effectiveness of the fault tolerance analysis of sorting networks.

Aims The aim of this study is that it is the systematic review of the analysis, design and the implementation of the web service security frameworks. This study is based on online banking networks. In the web application layer use of web service security framework on the development process and the use of software model to guide the development process. This study also analysed the web service security framework in which the following aspects have been covered authentication, confidentiality, integrity, and authorization. It also summarizes the web service security requirement with the use of transport security to protect the communication channel between web service provider and web service consumer. While the message level security ensures confidentiality by digitally encrypting. Objectives The objectives of this study are the following:

  • To evaluate the web services security framework.
  • To analyse, design and implementation of web service security framework.
  • To assess the application to application with use of the web platform which provided the interoperability for a heterogeneous software system.
  • To assess the web service security platform of online banking networks.

Aims This study aims that the novel analysis of deploying the adaptive web based learning environment software in colleges and school for the concept of building learning in the UK. The learning environment in this study evaluated by the software web based authoring tool and server. The environment designed to serve novices in acquiring both procedural and conceptual knowledge in the development. However, adaptivity implemented by the adaptive annotation link technology. This paper demonstrates the learning programming by programmers through the web based adaptive educational system called adaptive learning. The aim of this research is that in UK web based learning environment software for the concept building in students of schools and college. And considered the technological approach is better and the characteristics of the learners that need to be considered. Objectives The objectives of this study are the following:

  • To analyse the adaptive web based learning environment.
  • To assess the web based learning environment in school and college students of UK.
  • To evaluate the software for web based learning.
  • To assess the impact of web based learning environment software in school and college students in the UK.

Aims The aim of this study is that it is based on the novel approach of developing java programs and software for prediction and the management of applied financial systems. This study is based on a case study on stock markets. The financial predictive analytics software it produces the projection of future financial event based on the historical data patterns. There is various software for the prediction and management of the applied financial system. Softwares of the business forecasting it reduces the opportunity for the potential error. Objectives The objectives of this study are the following:

  • To analyse the development of the java programs and software for management and prediction.
  • To analyse the applied financial systems by the software.
  • To assess the impact of the java programs and software for prediction and management of applied financial systems of the case study on the stock markets.

Aim This study aims to evaluate the enhancement in materials object-oriented database (MOOD) metrics for the software maintainability and reliability. The organisations assess the maintainability of the software system before the deployed. However, object-oriented design is a useful technique to deliver and develop quality software. There are different types of the models and metrics software has been described and developed. It also proposes the maintainability model which is based on the analysis of the relationship between the object-oriented metrics and maintainability and reliability. Objectives: The objectives of this study are described below:

  • To evaluate the enhancement in Materials Object-Oriented Database (MOOD).
  • To assess the software maintainability and reliability.
  • To evaluate the enhancement in Materials Object-Oriented Database (MOOD) metrics for software maintainability and reliability.

Aims The aim of this study is that it is the systematic approach for assessing the dynamic technique with static metrics to check the coupling between software modules. Measurement plays a critical rule in the contemporary software deployment, development and used by the software engineer and enabling engineers to evaluate the software products efficiently. The extent of this research is that when compared dynamic technique with static metrics because this field is still growing and given the inherent advantages of the dynamic metrics. This study aims to investigate the research on dynamic software metrics to identify the issues associated with the design, implementation and selection and also check the coupling between software modules. Objectives: The objectives of this study are the following:

  • To discriminate the dynamic technique with the static metrics.
  • To assess the coupling between the software modules.

To observe the approach for assessing the dynamic technique with static metrics to check to couple between software modules.

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Research Topics & Ideas: CompSci & IT

50+ Computer Science Research Topic Ideas To Fast-Track Your Project

IT & Computer Science Research Topics

Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you’ve landed on this post, chances are you’re looking for a computer science-related research topic , but aren’t sure where to start. Here, we’ll explore a variety of CompSci & IT-related research ideas and topic thought-starters, including algorithms, AI, networking, database systems, UX, information security and software engineering.

NB – This is just the start…

The topic ideation and evaluation process has multiple steps . In this post, we’ll kickstart the process by sharing some research topic ideas within the CompSci domain. This is the starting point, but to develop a well-defined research topic, you’ll need to identify a clear and convincing research gap , along with a well-justified plan of action to fill that gap.

If you’re new to the oftentimes perplexing world of research, or if this is your first time undertaking a formal academic research project, be sure to check out our free dissertation mini-course. In it, we cover the process of writing a dissertation or thesis from start to end. Be sure to also sign up for our free webinar that explores how to find a high-quality research topic. 

Overview: CompSci Research Topics

  • Algorithms & data structures
  • Artificial intelligence ( AI )
  • Computer networking
  • Database systems
  • Human-computer interaction
  • Information security (IS)
  • Software engineering
  • Examples of CompSci dissertation & theses

Topics/Ideas: Algorithms & Data Structures

  • An analysis of neural network algorithms’ accuracy for processing consumer purchase patterns
  • A systematic review of the impact of graph algorithms on data analysis and discovery in social media network analysis
  • An evaluation of machine learning algorithms used for recommender systems in streaming services
  • A review of approximation algorithm approaches for solving NP-hard problems
  • An analysis of parallel algorithms for high-performance computing of genomic data
  • The influence of data structures on optimal algorithm design and performance in Fintech
  • A Survey of algorithms applied in internet of things (IoT) systems in supply-chain management
  • A comparison of streaming algorithm performance for the detection of elephant flows
  • A systematic review and evaluation of machine learning algorithms used in facial pattern recognition
  • Exploring the performance of a decision tree-based approach for optimizing stock purchase decisions
  • Assessing the importance of complete and representative training datasets in Agricultural machine learning based decision making.
  • A Comparison of Deep learning algorithms performance for structured and unstructured datasets with “rare cases”
  • A systematic review of noise reduction best practices for machine learning algorithms in geoinformatics.
  • Exploring the feasibility of applying information theory to feature extraction in retail datasets.
  • Assessing the use case of neural network algorithms for image analysis in biodiversity assessment

Topics & Ideas: Artificial Intelligence (AI)

  • Applying deep learning algorithms for speech recognition in speech-impaired children
  • A review of the impact of artificial intelligence on decision-making processes in stock valuation
  • An evaluation of reinforcement learning algorithms used in the production of video games
  • An exploration of key developments in natural language processing and how they impacted the evolution of Chabots.
  • An analysis of the ethical and social implications of artificial intelligence-based automated marking
  • The influence of large-scale GIS datasets on artificial intelligence and machine learning developments
  • An examination of the use of artificial intelligence in orthopaedic surgery
  • The impact of explainable artificial intelligence (XAI) on transparency and trust in supply chain management
  • An evaluation of the role of artificial intelligence in financial forecasting and risk management in cryptocurrency
  • A meta-analysis of deep learning algorithm performance in predicting and cyber attacks in schools

Research topic idea mega list

Topics & Ideas: Networking

  • An analysis of the impact of 5G technology on internet penetration in rural Tanzania
  • Assessing the role of software-defined networking (SDN) in modern cloud-based computing
  • A critical analysis of network security and privacy concerns associated with Industry 4.0 investment in healthcare.
  • Exploring the influence of cloud computing on security risks in fintech.
  • An examination of the use of network function virtualization (NFV) in telecom networks in Southern America
  • Assessing the impact of edge computing on network architecture and design in IoT-based manufacturing
  • An evaluation of the challenges and opportunities in 6G wireless network adoption
  • The role of network congestion control algorithms in improving network performance on streaming platforms
  • An analysis of network coding-based approaches for data security
  • Assessing the impact of network topology on network performance and reliability in IoT-based workspaces

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Topics & Ideas: Database Systems

  • An analysis of big data management systems and technologies used in B2B marketing
  • The impact of NoSQL databases on data management and analysis in smart cities
  • An evaluation of the security and privacy concerns of cloud-based databases in financial organisations
  • Exploring the role of data warehousing and business intelligence in global consultancies
  • An analysis of the use of graph databases for data modelling and analysis in recommendation systems
  • The influence of the Internet of Things (IoT) on database design and management in the retail grocery industry
  • An examination of the challenges and opportunities of distributed databases in supply chain management
  • Assessing the impact of data compression algorithms on database performance and scalability in cloud computing
  • An evaluation of the use of in-memory databases for real-time data processing in patient monitoring
  • Comparing the effects of database tuning and optimization approaches in improving database performance and efficiency in omnichannel retailing

Topics & Ideas: Human-Computer Interaction

  • An analysis of the impact of mobile technology on human-computer interaction prevalence in adolescent men
  • An exploration of how artificial intelligence is changing human-computer interaction patterns in children
  • An evaluation of the usability and accessibility of web-based systems for CRM in the fast fashion retail sector
  • Assessing the influence of virtual and augmented reality on consumer purchasing patterns
  • An examination of the use of gesture-based interfaces in architecture
  • Exploring the impact of ease of use in wearable technology on geriatric user
  • Evaluating the ramifications of gamification in the Metaverse
  • A systematic review of user experience (UX) design advances associated with Augmented Reality
  • A comparison of natural language processing algorithms automation of customer response Comparing end-user perceptions of natural language processing algorithms for automated customer response
  • Analysing the impact of voice-based interfaces on purchase practices in the fast food industry

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Topics & Ideas: Information Security

  • A bibliometric review of current trends in cryptography for secure communication
  • An analysis of secure multi-party computation protocols and their applications in cloud-based computing
  • An investigation of the security of blockchain technology in patient health record tracking
  • A comparative study of symmetric and asymmetric encryption algorithms for instant text messaging
  • A systematic review of secure data storage solutions used for cloud computing in the fintech industry
  • An analysis of intrusion detection and prevention systems used in the healthcare sector
  • Assessing security best practices for IoT devices in political offices
  • An investigation into the role social media played in shifting regulations related to privacy and the protection of personal data
  • A comparative study of digital signature schemes adoption in property transfers
  • An assessment of the security of secure wireless communication systems used in tertiary institutions

Topics & Ideas: Software Engineering

  • A study of agile software development methodologies and their impact on project success in pharmacology
  • Investigating the impacts of software refactoring techniques and tools in blockchain-based developments
  • A study of the impact of DevOps practices on software development and delivery in the healthcare sector
  • An analysis of software architecture patterns and their impact on the maintainability and scalability of cloud-based offerings
  • A study of the impact of artificial intelligence and machine learning on software engineering practices in the education sector
  • An investigation of software testing techniques and methodologies for subscription-based offerings
  • A review of software security practices and techniques for protecting against phishing attacks from social media
  • An analysis of the impact of cloud computing on the rate of software development and deployment in the manufacturing sector
  • Exploring the impact of software development outsourcing on project success in multinational contexts
  • An investigation into the effect of poor software documentation on app success in the retail sector

CompSci & IT Dissertations/Theses

While the ideas we’ve presented above are a decent starting point for finding a CompSci-related research topic, they are fairly generic and non-specific. So, it helps to look at actual dissertations and theses to see how this all comes together.

Below, we’ve included a selection of research projects from various CompSci-related degree programs to help refine your thinking. These are actual dissertations and theses, written as part of Master’s and PhD-level programs, so they can provide some useful insight as to what a research topic looks like in practice.

  • An array-based optimization framework for query processing and data analytics (Chen, 2021)
  • Dynamic Object Partitioning and replication for cooperative cache (Asad, 2021)
  • Embedding constructural documentation in unit tests (Nassif, 2019)
  • PLASA | Programming Language for Synchronous Agents (Kilaru, 2019)
  • Healthcare Data Authentication using Deep Neural Network (Sekar, 2020)
  • Virtual Reality System for Planetary Surface Visualization and Analysis (Quach, 2019)
  • Artificial neural networks to predict share prices on the Johannesburg stock exchange (Pyon, 2021)
  • Predicting household poverty with machine learning methods: the case of Malawi (Chinyama, 2022)
  • Investigating user experience and bias mitigation of the multi-modal retrieval of historical data (Singh, 2021)
  • Detection of HTTPS malware traffic without decryption (Nyathi, 2022)
  • Redefining privacy: case study of smart health applications (Al-Zyoud, 2019)
  • A state-based approach to context modeling and computing (Yue, 2019)
  • A Novel Cooperative Intrusion Detection System for Mobile Ad Hoc Networks (Solomon, 2019)
  • HRSB-Tree for Spatio-Temporal Aggregates over Moving Regions (Paduri, 2019)

Looking at these titles, you can probably pick up that the research topics here are quite specific and narrowly-focused , compared to the generic ones presented earlier. This is an important thing to keep in mind as you develop your own research topic. That is to say, to create a top-notch research topic, you must be precise and target a specific context with specific variables of interest . In other words, you need to identify a clear, well-justified research gap.

Fast-Track Your Research Topic

If you’re still feeling a bit unsure about how to find a research topic for your Computer Science dissertation or research project, check out our Topic Kickstarter service.

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dissertation topics for software systems

39 Information Systems Dissertation Topics Ideas

As the name depicts, information systems dissertation topics revolve around the information technology sphere of organizations and industries. Information systems research topics include both primary as well as secondary levels of research studies and their complexities differ in accordance with the academic and degree levels at hand. Other Related Post Computer science dissertation topics Internet […]

Information Systems Dissertation Topics

As the name depicts, information systems dissertation topics revolve around the information technology sphere of organizations and industries. Information systems research topics include both primary as well as secondary levels of research studies and their complexities differ in accordance with the academic and degree levels at hand.

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  • IT dissertation topics
  • Computer science research topics

Best Information Systems Dissertation Topics Ideas for College Students

Given below is an extensive and enriched list of information systems thesis topics for our clients so that they go through the list and find something as per their interest and priority:

  • A historical analysis of information systems management: focus on the past three decades.
  • The role played by leadership, alignment, and planning in the domain of information systems management.
  • Research in information systems management: focus on post-COVID time period.
  • International information systems management: potential challenges and risks involved.
  • Information policy and international information systems management: a systematic analysis.
  • Information systems management and global operations: a review of the literature.
  • Importance of case studies and integrated projects in teaching information systems management.
  • A comparative analysis of practitioners and academicians in the field of information systems management.
  • How information technology supports businesses: the role played by information systems management.
  • Information systems management practices: a descriptive analysis.
  • Information systems management and the public sector: focus on the key issues.
  • Utilization of consumer internet data: ethics in information systems management.
  • Software development: groupware and problem-solving in a correlational analysis.
  • Research in the field of information systems management: focus on new innovations and ideas.
  • Cognition digital twins for personalized information systems of smart cities: Proof of concept
  • Information management systems: comparing private and public organizations in country X.
  • Machine learning-based diagnosis of diseases using the unfolded EEG spectra: toward an intelligent software sensor.
  • Relationship between information systems management and risk management systems: a comparative analysis.
  • Judging the IT department performance in an organization through information systems management.
  • Information systems management graduate school curriculums: a descriptive study.
  • Relationship between organizational learning and information systems management: a systematic analysis.
  • Quality management in the domain of information systems: a descriptive analysis.
  • Management of big data in developing countries of the world: a review of the literature.
  • Strategic information systems management: focus on the role of a balanced scorecard.
  • Delivery of information system: formation of a hypothetical framework.
  • Information quality management framework: a review of the literature.
  • Information systems hierarchy: a systematic analysis.
  • Importance of big data and business intelligence for the sustainable development in organizations: a UK-based approach.
  • Correlation between information systems management and risk management infrastructure to attain business risk resilience.
  • Effects of COVID-19 pandemic on the information systems management of X country.
  • Role of structured versus unstructured data in the domain of information systems management.
  • Business intelligence and information systems management: a review of the literature.
  • Effects of information systems on organizational performance: pre and post COVID analysis.
  • The Determinants of management information systems effectiveness in small-and medium-sized enterprises.
  • IT governance implementation and information systems management.
  • IS strategic planning and management services: a descriptive review.
  • Information system security at international levels: a review of the literature.
  • Developing a hypothetical model for measuring quality in information systems management.
  • The effects of information systems compatibility on firm performance following mergers and acquisitions
  • Implications of Knowledge Organization Systems for Health Information Exchange and Communication during the COVID-19 Pandemic

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dissertation topics for software systems

How to Contact Faculty for IW/Thesis Advising

Send the professor an e-mail. When you write a professor, be clear that you want a meeting regarding a senior thesis or one-on-one IW project, and briefly describe the topic or idea that you want to work on. Check the faculty listing for email addresses.

Parastoo Abtahi, Room 419

Available for single-semester IW and senior thesis advising, 2023-2024

  • Research Areas: Human-Computer Interaction (HCI), Augmented Reality (AR), and Spatial Computing
  • Input techniques for on-the-go interaction (e.g., eye-gaze, microgestures, voice) with a focus on uncertainty, disambiguation, and privacy.
  • Minimal and timely multisensory output (e.g., spatial audio, haptics) that enables users to attend to their physical environment and the people around them, instead of a 2D screen.
  • Interaction with intelligent systems (e.g., IoT, robots) situated in physical spaces with a focus on updating users’ mental model despite the complexity and dynamicity of these systems.

Ryan Adams, Room 411

Research areas:

  • Machine learning driven design
  • Generative models for structured discrete objects
  • Approximate inference in probabilistic models
  • Accelerating solutions to partial differential equations
  • Innovative uses of automatic differentiation
  • Modeling and optimizing 3d printing and CNC machining

Andrew Appel, Room 209

  • Research Areas: Formal methods, programming languages, compilers, computer security.
  • Software verification (for which taking COS 326 / COS 510 is helpful preparation)
  • Game theory of poker or other games (for which COS 217 / 226 are helpful)
  • Computer game-playing programs (for which COS 217 / 226)
  •  Risk-limiting audits of elections (for which ORF 245 or other knowledge of probability is useful)

Sanjeev Arora, Room 407

  • Theoretical machine learning, deep learning and its analysis, natural language processing. My advisees would typically have taken a course in algorithms (COS423 or COS 521 or equivalent) and a course in machine learning.
  • Show that finding approximate solutions to NP-complete problems is also NP-complete (i.e., come up with NP-completeness reductions a la COS 487). 
  • Experimental Algorithms: Implementing and Evaluating Algorithms using existing software packages. 
  • Studying/designing provable algorithms for machine learning and implementions using packages like scipy and MATLAB, including applications in Natural language processing and deep learning.
  • Any topic in theoretical computer science.

David August, Room 221

  • Research Areas: Computer Architecture, Compilers, Parallelism
  • Containment-based approaches to security:  We have designed and tested a simple hardware+software containment mechanism that stops incorrect communication resulting from faults, bugs, or exploits from leaving the system.   Let's explore ways to use containment to solve real problems.  Expect to work with corporate security and technology decision-makers.
  • Parallelism: Studies show much more parallelism than is currently realized in compilers and architectures.  Let's find ways to realize this parallelism.
  • Any other interesting topic in computer architecture or compilers. 

Mark Braverman, 194 Nassau St., Room 231

Available for Spring 2024 single-semester IW, only

  • Research Areas: computational complexity, algorithms, applied probability, computability over the real numbers, game theory and mechanism design, information theory.
  • Topics in computational and communication complexity.
  • Applications of information theory in complexity theory.
  • Algorithms for problems under real-life assumptions.
  • Game theory, network effects
  • Mechanism design (could be on a problem proposed by the student)

Sebastian Caldas, 221 Nassau Street, Room 105

  • Research Areas: collaborative learning, machine learning for healthcare. Typically, I will work with students that have taken COS324.
  • Methods for collaborative and continual learning.
  • Machine learning for healthcare applications.

Bernard Chazelle, 194 Nassau St., Room 301

  • Research Areas: Natural Algorithms, Computational Geometry, Sublinear Algorithms. 
  • Natural algorithms (flocking, swarming, social networks, etc).
  • Sublinear algorithms
  • Self-improving algorithms
  • Markov data structures

Danqi Chen, Room 412

Not available for IW or thesis advising, 2023-2024

  • My advisees would be expected to have taken a course in machine learning and ideally have taken COS484 or an NLP graduate seminar.
  • Representation learning for text and knowledge bases
  • Pre-training and transfer learning
  • Question answering and reading comprehension
  • Information extraction
  • Text summarization
  • Any other interesting topics related to natural language understanding/generation

Marcel Dall'Agnol, Corwin 034

Available for single-semester and senior thesis advising, 2023-2024

  • Research Areas: Theoretical computer science. (Specifically, quantum computation, sublinear algorithms, complexity theory, interactive proofs and cryptography)

Jia Deng, Room 423

Available for Fall 2023 single-semester IW, only

  •  Research Areas: Computer Vision, Machine Learning.
  • Object recognition and action recognition
  • Deep Learning, autoML, meta-learning
  • Geometric reasoning, logical reasoning

Adji Bousso Dieng, Room 406

  • Research areas: Vertaix is a research lab at Princeton University led by Professor Adji Bousso Dieng. We work at the intersection of artificial intelligence (AI) and the natural sciences. The models and algorithms we develop are motivated by problems in those domains and contribute to advancing methodological research in AI. We leverage tools in statistical machine learning and deep learning in developing methods for learning with the data, of various modalities, arising from the natural sciences.

Robert Dondero, Corwin Hall, Room 038

  • Research Areas:  Software engineering; software engineering education.
  • Develop or evaluate tools to facilitate student learning in undergraduate computer science courses at Princeton, and beyond.
  • In particular, can code critiquing tools help students learn about software quality?

Zeev Dvir, 194 Nassau St., Room 250

Not available for IW or thesis advising, 2023-2024.

  • Research Areas: computational complexity, pseudo-randomness, coding theory and discrete mathematics.
  • Independent Research: I have various research problems related to Pseudorandomness, Coding theory, Complexity and Discrete mathematics - all of which require strong mathematical background. A project could also be based on writing a survey paper describing results from a few theory papers revolving around some particular subject.

Benjamin Eysenbach, Room 416

  • Research areas: reinforcement learning, machine learning. My advisees would typically have taken COS324.
  • Using RL algorithms to applications in science and engineering.
  • Emergent behavior of RL algorithms on high-fidelity robotic simulators.
  • Studying how architectures and representations can facilitate generalization.

Christiane Fellbaum, 1-S-14 Green

No longer available for single-term IW and senior thesis advising, 2023-2024

  • Research Areas: theoretical and computational linguistics, word sense disambiguation, lexical resource construction, English and multilingual WordNet(s), ontology
  • Anything having to do with natural language--come and see me with/for ideas suitable to your background and interests. Some topics students have worked on in the past:
  • Developing parsers, part-of-speech taggers, morphological analyzers for underrepresented languages (you don't have to know the language to develop such tools!)
  • Quantitative approaches to theoretical linguistics questions
  • Extensions and interfaces for WordNet (English and WN in other languages),
  • Applications of WordNet(s), including:
  • Foreign language tutoring systems,
  • Spelling correction software,
  • Word-finding/suggestion software for ordinary users and people with memory problems,
  • Machine Translation 
  • Sentiment and Opinion detection
  • Automatic reasoning and inferencing
  • Collaboration with professors in the social sciences and humanities ("Digital Humanities")

Adam Finkelstein, Room 424 

  • Research Areas: computer graphics, audio.

Robert S. Fish, Corwin Hall, Room 037

No longer available for single-semester IW and senior thesis advising, 2023-2024

  • Networking and telecommunications
  • Learning, perception, and intelligence, artificial and otherwise;
  • Human-computer interaction and computer-supported cooperative work
  • Online education, especially in Computer Science Education
  • Topics in research and development innovation methodologies including standards, open-source, and entrepreneurship
  • Distributed autonomous organizations and related blockchain technologies

Michael Freedman, Room 308 

  • Research Areas: Distributed systems, security, networking
  • Projects related to streaming data analysis, datacenter systems and networks, untrusted cloud storage and applications. Please see my group website at http://sns.cs.princeton.edu/ for current research projects.

Ruth Fong, Room 032

  • Research Areas: computer vision, machine learning, deep learning, interpretability, explainable AI, fairness and bias in AI
  • Develop a technique for understanding AI models
  • Design a AI model that is interpretable by design
  • Build a paradigm for detecting and/or correcting failure points in an AI model
  • Analyze an existing AI model and/or dataset to better understand its failure points
  • Build a computer vision system for another domain (e.g., medical imaging, satellite data, etc.)
  • Develop a software package for explainable AI
  • Adapt explainable AI research to a consumer-facing problem

Note: I am happy to advise any project if there's a sufficient overlap in interest and/or expertise; please reach out via email to chat about project ideas.

Tom Griffiths, Room 405

Research areas: computational cognitive science, computational social science, machine learning and artificial intelligence

Note: I am open to projects that apply ideas from computer science to understanding aspects of human cognition in a wide range of areas, from decision-making to cultural evolution and everything in between. For example, we have current projects analyzing chess game data and magic tricks, both of which give us clues about how human minds work. Students who have expertise or access to data related to games, magic, strategic sports like fencing, or other quantifiable domains of human behavior feel free to get in touch.

Aarti Gupta, Room 220

  • Research Areas: Formal methods, program analysis, logic decision procedures
  • Finding bugs in open source software using automatic verification tools
  • Software verification (program analysis, model checking, test generation)
  • Decision procedures for logical reasoning (SAT solvers, SMT solvers)

Elad Hazan, Room 409  

  • Research interests: machine learning methods and algorithms, efficient methods for mathematical optimization, regret minimization in games, reinforcement learning, control theory and practice
  • Machine learning, efficient methods for mathematical optimization, statistical and computational learning theory, regret minimization in games.
  • Implementation and algorithm engineering for control, reinforcement learning and robotics
  • Implementation and algorithm engineering for time series prediction

Felix Heide, Room 410

  • Research Areas: Computational Imaging, Computer Vision, Machine Learning (focus on Optimization and Approximate Inference).
  • Optical Neural Networks
  • Hardware-in-the-loop Holography
  • Zero-shot and Simulation-only Learning
  • Object recognition in extreme conditions
  • 3D Scene Representations for View Generation and Inverse Problems
  • Long-range Imaging in Scattering Media
  • Hardware-in-the-loop Illumination and Sensor Optimization
  • Inverse Lidar Design
  • Phase Retrieval Algorithms
  • Proximal Algorithms for Learning and Inference
  • Domain-Specific Language for Optics Design

Kyle Jamieson, Room 306

  • Research areas: Wireless and mobile networking; indoor radar and indoor localization; Internet of Things
  • See other topics on my independent work  ideas page  (campus IP and CS dept. login req'd)

Alan Kaplan, 221 Nassau Street, Room 105

Research Areas:

  • Random apps of kindness - mobile application/technology frameworks used to help individuals or communities; topic areas include, but are not limited to: first response, accessibility, environment, sustainability, social activism, civic computing, tele-health, remote learning, crowdsourcing, etc.
  • Tools automating programming language interoperability - Java/C++, React Native/Java, etc.
  • Software visualization tools for education
  • Connected consumer devices, applications and protocols

Brian Kernighan, Room 311

  • Research Areas: application-specific languages, document preparation, user interfaces, software tools, programming methodology
  • Application-oriented languages, scripting languages.
  • Tools; user interfaces
  • Digital humanities

Zachary Kincaid, Room 219

  • Research areas: programming languages, program analysis, program verification, automated reasoning
  • Independent Research Topics:
  • Develop a practical algorithm for an intractable problem (e.g., by developing practical search heuristics, or by reducing to, or by identifying a tractable sub-problem, ...).
  • Design a domain-specific programming language, or prototype a new feature for an existing language.
  • Any interesting project related to programming languages or logic.

Gillat Kol, Room 316

Aleksandra korolova, 309 sherrerd hall.

Available for single-term IW and senior thesis advising, 2023-2024

  • Research areas: Societal impacts of algorithms and AI; privacy; fair and privacy-preserving machine learning; algorithm auditing.

Advisees typically have taken one or more of COS 226, COS 324, COS 423, COS 424 or COS 445.

Amit Levy, Room 307

  • Research Areas: Operating Systems, Distributed Systems, Embedded Systems, Internet of Things
  • Distributed hardware testing infrastructure
  • Second factor security tokens
  • Low-power wireless network protocol implementation
  • USB device driver implementation

Kai Li, Room 321

  • Research Areas: Distributed systems; storage systems; content-based search and data analysis of large datasets.
  • Fast communication mechanisms for heterogeneous clusters.
  • Approximate nearest-neighbor search for high dimensional data.
  • Data analysis and prediction of in-patient medical data.
  • Optimized implementation of classification algorithms on manycore processors.

Xiaoyan Li, 221 Nassau Street, Room 104

  • Research areas: Information retrieval, novelty detection, question answering, AI, machine learning and data analysis.
  • Explore new statistical retrieval models for document retrieval and question answering.
  • Apply AI in various fields.
  • Apply supervised or unsupervised learning in health, education, finance, and social networks, etc.
  • Any interesting project related to AI, machine learning, and data analysis.

Wyatt Lloyd, Room 323

  • Research areas: Distributed Systems
  • Caching algorithms and implementations
  • Storage systems
  • Distributed transaction algorithms and implementations

Margaret Martonosi, Room 208

  • Quantum Computing research, particularly related to architecture and compiler issues for QC.
  • Computer architectures specialized for modern workloads (e.g., graph analytics, machine learning algorithms, mobile applications
  • Investigating security and privacy vulnerabilities in computer systems, particularly IoT devices.
  • Other topics in computer architecture or mobile / IoT systems also possible.

Jonathan Mayer, Sherrerd Hall, Room 307 

  • Research areas: Technology law and policy, with emphasis on national security, criminal procedure, consumer privacy, network management, and online speech.
  • Assessing the effects of government policies, both in the public and private sectors.
  • Collecting new data that relates to government decision making, including surveying current business practices and studying user behavior.
  • Developing new tools to improve government processes and offer policy alternatives.

Andrés Monroy-Hernández, Room 405

  • Research Areas: Human-Computer Interaction, Social Computing, Public-Interest Technology, Augmented Reality, Urban Computing
  • Research interests:developing public-interest socio-technical systems.  We are currently creating alternatives to gig work platforms that are more equitable for all stakeholders. For instance, we are investigating the socio-technical affordances necessary to support a co-op food delivery network owned and managed by workers and restaurants. We are exploring novel system designs that support self-governance, decentralized/federated models, community-centered data ownership, and portable reputation systems.  We have opportunities for students interested in human-centered computing, UI/UX design, full-stack software development, and qualitative/quantitative user research.
  • Beyond our core projects, we are open to working on research projects that explore the use of emerging technologies, such as AR, wearables, NFTs, and DAOs, for creative and out-of-the-box applications.

Christopher Moretti, Corwin Hall, Room 036

  • Research areas: Distributed systems, high-throughput computing, computer science/engineering education
  • Expansion, improvement, and evaluation of open-source distributed computing software.
  • Applications of distributed computing for "big science" (e.g. biometrics, data mining, bioinformatics)
  • Software and best practices for computer science education and study, especially Princeton's 126/217/226 sequence or MOOCs development
  • Sports analytics and/or crowd-sourced computing

Radhika Nagpal, F316 Engineering Quadrangle

  • Research areas: control, robotics and dynamical systems

Karthik Narasimhan, Room 422

  • Research areas: Natural Language Processing, Reinforcement Learning
  • Autonomous agents for text-based games ( https://www.microsoft.com/en-us/research/project/textworld/ )
  • Transfer learning/generalization in NLP
  • Techniques for generating natural language
  • Model-based reinforcement learning

Arvind Narayanan, 308 Sherrerd Hall 

Research Areas: fair machine learning (and AI ethics more broadly), the social impact of algorithmic systems, tech policy

Pedro Paredes, Corwin Hall, Room 041

My primary research work is in Theoretical Computer Science.

 * Research Interest: Spectral Graph theory, Pseudorandomness, Complexity theory, Coding Theory, Quantum Information Theory, Combinatorics.

The IW projects I am interested in advising can be divided into three categories:

 1. Theoretical research

I am open to advise work on research projects in any topic in one of my research areas of interest. A project could also be based on writing a survey given results from a few papers. Students should have a solid background in math (e.g., elementary combinatorics, graph theory, discrete probability, basic algebra/calculus) and theoretical computer science (226 and 240 material, like big-O/Omega/Theta, basic complexity theory, basic fundamental algorithms). Mathematical maturity is a must.

A (non exhaustive) list of topics of projects I'm interested in:   * Explicit constructions of better vertex expanders and/or unique neighbor expanders.   * Construction deterministic or random high dimensional expanders.   * Pseudorandom generators for different problems.   * Topics around the quantum PCP conjecture.   * Topics around quantum error correcting codes and locally testable codes, including constructions, encoding and decoding algorithms.

 2. Theory informed practical implementations of algorithms   Very often the great advances in theoretical research are either not tested in practice or not even feasible to be implemented in practice. Thus, I am interested in any project that consists in trying to make theoretical ideas applicable in practice. This includes coming up with new algorithms that trade some theoretical guarantees for feasible implementation yet trying to retain the soul of the original idea; implementing new algorithms in a suitable programming language; and empirically testing practical implementations and comparing them with benchmarks / theoretical expectations. A project in this area doesn't have to be in my main areas of research, any theoretical result could be suitable for such a project.

Some examples of areas of interest:   * Streaming algorithms.   * Numeric linear algebra.   * Property testing.   * Parallel / Distributed algorithms.   * Online algorithms.    3. Machine learning with a theoretical foundation

I am interested in projects in machine learning that have some mathematical/theoretical, even if most of the project is applied. This includes topics like mathematical optimization, statistical learning, fairness and privacy.

One particular area I have been recently interested in is in the area of rating systems (e.g., Chess elo) and applications of this to experts problems.

Final Note: I am also willing to advise any project with any mathematical/theoretical component, even if it's not the main one; please reach out via email to chat about project ideas.

Iasonas Petras, Corwin Hall, Room 033

  • Research Areas: Information Based Complexity, Numerical Analysis, Quantum Computation.
  • Prerequisites: Reasonable mathematical maturity. In case of a project related to Quantum Computation a certain familiarity with quantum mechanics is required (related courses: ELE 396/PHY 208).
  • Possible research topics include:

1.   Quantum algorithms and circuits:

  • i. Design or simulation quantum circuits implementing quantum algorithms.
  • ii. Design of quantum algorithms solving/approximating continuous problems (such as Eigenvalue problems for Partial Differential Equations).

2.   Information Based Complexity:

  • i. Necessary and sufficient conditions for tractability of Linear and Linear Tensor Product Problems in various settings (for example worst case or average case). 
  • ii. Necessary and sufficient conditions for tractability of Linear and Linear Tensor Product Problems under new tractability and error criteria.
  • iii. Necessary and sufficient conditions for tractability of Weighted problems.
  • iv. Necessary and sufficient conditions for tractability of Weighted Problems under new tractability and error criteria.

3. Topics in Scientific Computation:

  • i. Randomness, Pseudorandomness, MC and QMC methods and their applications (Finance, etc)

Yuri Pritykin, 245 Carl Icahn Lab

  • Research interests: Computational biology; Cancer immunology; Regulation of gene expression; Functional genomics; Single-cell technologies.
  • Potential research projects: Development, implementation, assessment and/or application of algorithms for analysis, integration, interpretation and visualization of multi-dimensional data in molecular biology, particularly single-cell and spatial genomics data.

Benjamin Raphael, Room 309  

  • Research interests: Computational biology and bioinformatics; Cancer genomics; Algorithms and machine learning approaches for analysis of large-scale datasets
  • Implementation and application of algorithms to infer evolutionary processes in cancer
  • Identifying correlations between combinations of genomic mutations in human and cancer genomes
  • Design and implementation of algorithms for genome sequencing from new DNA sequencing technologies
  • Graph clustering and network anomaly detection, particularly using diffusion processes and methods from spectral graph theory

Vikram Ramaswamy, 035 Corwin Hall

  • Research areas: Interpretability of AI systems, Fairness in AI systems, Computer vision.
  • Constructing a new method to explain a model / create an interpretable by design model
  • Analyzing a current model / dataset to understand bias within the model/dataset
  • Proposing new fairness evaluations
  • Proposing new methods to train to improve fairness
  • Developing synthetic datasets for fairness / interpretability benchmarks
  • Understanding robustness of models

Ran Raz, Room 240

  • Research Area: Computational Complexity
  • Independent Research Topics: Computational Complexity, Information Theory, Quantum Computation, Theoretical Computer Science

Szymon Rusinkiewicz, Room 406

  • Research Areas: computer graphics; computer vision; 3D scanning; 3D printing; robotics; documentation and visualization of cultural heritage artifacts
  • Research ways of incorporating rotation invariance into computer visiontasks such as feature matching and classification
  • Investigate approaches to robust 3D scan matching
  • Model and compensate for imperfections in 3D printing
  • Given a collection of small mobile robots, apply control policies learned in simulation to the real robots.

Olga Russakovsky, Room 408

  • Research Areas: computer vision, machine learning, deep learning, crowdsourcing, fairness&bias in AI
  • Design a semantic segmentation deep learning model that can operate in a zero-shot setting (i.e., recognize and segment objects not seen during training)
  • Develop a deep learning classifier that is impervious to protected attributes (such as gender or race) that may be erroneously correlated with target classes
  • Build a computer vision system for the novel task of inferring what object (or part of an object) a human is referring to when pointing to a single pixel in the image. This includes both collecting an appropriate dataset using crowdsourcing on Amazon Mechanical Turk, creating a new deep learning formulation for this task, and running extensive analysis of both the data and the model

Sebastian Seung, Princeton Neuroscience Institute, Room 153

  • Research Areas: computational neuroscience, connectomics, "deep learning" neural networks, social computing, crowdsourcing, citizen science
  • Gamification of neuroscience (EyeWire  2.0)
  • Semantic segmentation and object detection in brain images from microscopy
  • Computational analysis of brain structure and function
  • Neural network theories of brain function

Jaswinder Pal Singh, Room 324

  • Research Areas: Boundary of technology and business/applications; building and scaling technology companies with special focus at that boundary; parallel computing systems and applications: parallel and distributed applications and their implications for software and architectural design; system software and programming environments for multiprocessors.
  • Develop a startup company idea, and build a plan/prototype for it.
  • Explore tradeoffs at the boundary of technology/product and business/applications in a chosen area.
  • Study and develop methods to infer insights from data in different application areas, from science to search to finance to others. 
  • Design and implement a parallel application. Possible areas include graphics, compression, biology, among many others. Analyze performance bottlenecks using existing tools, and compare programming models/languages.
  • Design and implement a scalable distributed algorithm.

Mona Singh, Room 420

  • Research Areas: computational molecular biology, as well as its interface with machine learning and algorithms.
  • Whole and cross-genome methods for predicting protein function and protein-protein interactions.
  • Analysis and prediction of biological networks.
  • Computational methods for inferring specific aspects of protein structure from protein sequence data.
  • Any other interesting project in computational molecular biology.

Robert Tarjan, 194 Nassau St., Room 308

Available for single-semester IW and senior thesis advising, 2022-2023

  • Research Areas: Data structures; graph algorithms; combinatorial optimization; computational complexity; computational geometry; parallel algorithms.
  • Implement one or more data structures or combinatorial algorithms to provide insight into their empirical behavior.
  • Design and/or analyze various data structures and combinatorial algorithms.

Olga Troyanskaya, Room 320

  • Research Areas: Bioinformatics; analysis of large-scale biological data sets (genomics, gene expression, proteomics, biological networks); algorithms for integration of data from multiple data sources; visualization of biological data; machine learning methods in bioinformatics.
  • Implement and evaluate one or more gene expression analysis algorithm.
  • Develop algorithms for assessment of performance of genomic analysis methods.
  • Develop, implement, and evaluate visualization tools for heterogeneous biological data.

David Walker, Room 211

  • Research Areas: Programming languages, type systems, compilers, domain-specific languages, software-defined networking and security
  • Independent Research Topics:  Any other interesting project that involves humanitarian hacking, functional programming, domain-specific programming languages, type systems, compilers, software-defined networking, fault tolerance, language-based security, theorem proving, logic or logical frameworks.

Shengyi Wang, Postdoctoral Research Associate, Room 216

  • Independent Research topics: Explore Escher-style tilings using (introductory) group theory and automata theory to produce beautiful pictures.

Kevin Wayne, Corwin Hall, Room 040

  • Research Areas: design, analysis, and implementation of algorithms; data structures; combinatorial optimization; graphs and networks.
  • Design and implement computer visualizations of algorithms or data structures.
  • Develop pedagogical tools or programming assignments for the computer science curriculum at Princeton and beyond.
  • Develop assessment infrastructure and assessments for MOOCs.

Matt Weinberg, 194 Nassau St., Room 222

  • Research Areas: algorithms, algorithmic game theory, mechanism design, game theoretical problems in {Bitcoin, networking, healthcare}.
  • Theoretical questions related to COS 445 topics such as matching theory, voting theory, auction design, etc. 
  • Theoretical questions related to incentives in applications like Bitcoin, the Internet, health care, etc. In a little bit more detail: protocols for these systems are often designed assuming that users will follow them. But often, users will actually be strictly happier to deviate from the intended protocol. How should we reason about user behavior in these protocols? How should we design protocols in these settings?

Huacheng Yu, Room 310

  • data structures
  • streaming algorithms
  • design and analyze data structures / streaming algorithms
  • prove impossibility results (lower bounds)
  • implement and evaluate data structures / streaming algorithms

Ellen Zhong, Room 314

No longer available for single-term IW  and senior thesis advising, 2023-2024

Opportunities outside the department

We encourage students to look in to doing interdisciplinary computer science research and to work with professors in departments other than computer science.  However, every CS independent work project must have a strong computer science element (even if it has other scientific or artistic elements as well.)  To do a project with an adviser outside of computer science you must have permission of the department.  This can be accomplished by having a second co-adviser within the computer science department or by contacting the independent work supervisor about the project and having he or she sign the independent work proposal form.

Here is a list of professors outside the computer science department who are eager to work with computer science undergraduates.

Maria Apostolaki, Engineering Quadrangle, C330

  • Research areas: Computing & Networking, Data & Information Science, Security & Privacy

Branko Glisic, Engineering Quadrangle, Room E330

  • Documentation of historic structures
  • Cyber physical systems for structural health monitoring
  • Developing virtual and augmented reality applications for documenting structures
  • Applying machine learning techniques to generate 3D models from 2D plans of buildings
  •  Contact : Rebecca Napolitano, rkn2 (@princeton.edu)

Mihir Kshirsagar, Sherrerd Hall, Room 315

Center for Information Technology Policy.

  • Consumer protection
  • Content regulation
  • Competition law
  • Economic development
  • Surveillance and discrimination

Sharad Malik, Engineering Quadrangle, Room B224

Select a Senior Thesis Adviser for the 2020-21 Academic Year.

  • Design of reliable hardware systems
  • Verifying complex software and hardware systems

Prateek Mittal, Engineering Quadrangle, Room B236

  • Internet security and privacy 
  • Social Networks
  • Privacy technologies, anonymous communication
  • Network Science
  • Internet security and privacy: The insecurity of Internet protocols and services threatens the safety of our critical network infrastructure and billions of end users. How can we defend end users as well as our critical network infrastructure from attacks?
  • Trustworthy social systems: Online social networks (OSNs) such as Facebook, Google+, and Twitter have revolutionized the way our society communicates. How can we leverage social connections between users to design the next generation of communication systems?
  • Privacy Technologies: Privacy on the Internet is eroding rapidly, with businesses and governments mining sensitive user information. How can we protect the privacy of our online communications? The Tor project (https://www.torproject.org/) is a potential application of interest.

Ken Norman,  Psychology Dept, PNI 137

  • Research Areas: Memory, the brain and computation 
  • Lab:  Princeton Computational Memory Lab

Potential research topics

  • Methods for decoding cognitive state information from neuroimaging data (fMRI and EEG) 
  • Neural network simulations of learning and memory

Caroline Savage

Office of Sustainability, Phone:(609)258-7513, Email: cs35 (@princeton.edu)

The  Campus as Lab  program supports students using the Princeton campus as a living laboratory to solve sustainability challenges. The Office of Sustainability has created a list of campus as lab research questions, filterable by discipline and topic, on its  website .

An example from Computer Science could include using  TigerEnergy , a platform which provides real-time data on campus energy generation and consumption, to study one of the many energy systems or buildings on campus. Three CS students used TigerEnergy to create a  live energy heatmap of campus .

Other potential projects include:

  • Apply game theory to sustainability challenges
  • Develop a tool to help visualize interactions between complex campus systems, e.g. energy and water use, transportation and storm water runoff, purchasing and waste, etc.
  • How can we learn (in aggregate) about individuals’ waste, energy, transportation, and other behaviors without impinging on privacy?

Janet Vertesi, Sociology Dept, Wallace Hall, Room 122

  • Research areas: Sociology of technology; Human-computer interaction; Ubiquitous computing.
  • Possible projects: At the intersection of computer science and social science, my students have built mixed reality games, produced artistic and interactive installations, and studied mixed human-robot teams, among other projects.

David Wentzlaff, Engineering Quadrangle, Room 228

Computing, Operating Systems, Sustainable Computing.

  • Instrument Princeton's Green (HPCRC) data center
  • Investigate power utilization on an processor core implemented in an FPGA
  • Dismantle and document all of the components in modern electronics. Invent new ways to build computers that can be recycled easier.
  • Other topics in parallel computer architecture or operating systems

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Theses and Projects

We are always looking for enthusiastic students willing to work on our research projects. We are also open for your own ideas. Just fill out this form . We are going to contact you as soon as possible.

Open Topics

We don't necessarily advertise all current research topics. Use the websites of our scientific staff to obtain information about their research.

Or propose your own topic: application

Offered MSc Thesis topics

See also our current list of projects on the Research page to get an idea of what is topical in our research. Another list of all our projects is also available in Tuhat, with responsible persons listed (you can ask them about potential thesis topics).

A more exhaustive list of topics from the department is available at CSM Master thesis topics .

General writing Instructions

We have written some instructions to help the students write their Master's theses, seminar papers and B.Sc. theses. Please, read the guide before starting your thesis work: Scientific Writing – Guide of the Empirical Software Engineering Research Group .

Master's Thesis Topics

Software engineering and technology are prevalent areas for thesis at the department, and many candidates ask for thesis topics every academic year. We do our best to accommodate the requests, but the applicants can smoothen the process by taking an active role in thinking about potential topics based on the themes presented below.

We provide guidance for selecting a suitable topic and the supervision and support needed to complete the work. Please contact Antti-Pekka Tuovinen or Tomi Männistö if you are interested. You can also contact the group members to ask about the subject areas they are working on.

Suppose you, as a student, are working in software development, processes, architecture or something related. In that case, there is a good chance of finding an interesting thesis topic that closely relates to your work. In such a case, the actual work often provides an excellent problem to investigate, propose or try out potential solutions for, or the case can act as a rich source of data about the practice of software development.

We also welcome companies to suggest potential topics for Master's thesis. The topics can be general, based on existing research, or they may require original research and problem-solving. We will help to evaluate and fine-tune the proposals. Depending on the topic, you may also need to be prepared to provide guidance and assistance during the thesis project.

Please contact Antti-Pekka Tuovinen or Tomi Männistö if you have an idea for an industrial thesis and need further information.

The listing below introduces our current research areas and potential topics for the thesis. Each topic has a short description and the names of the researchers working on the topic. Please contact them for more details about the research and thesis work. Note that you can also suggest and discuss other topics within the general area of software engineering research. We encourage creativity and student-centred insight in selecting and defining the topic.

Earlier theses

Some earlier MSc thesis titles below give some idea about the topics. You can try looking up more info from E-thesis , but note that it is up to the author if the actual thesis pdf is available online. Just search using the title (or part of it) in quotation marks. You can also go to the library in person and read all theses (even those without a public pdf) on a kiosk workstation (ask the staff if you need help).

  • Exploring study paths and study success in undergraduate Computer Science studies
  • EU:n tietosuoja-asetuksen GDPR:n vaikutus suomalaisissa pk-yrityksissä 2018-2020
  • Industrial Surveys on Software Testing Practices: A Literature Review
  • Laskennallisesti raskaan simulointiohjelmistokomponentin korvaaminen reaaliaikasovelluksessa koneoppimismenetelmällä
  • Web service monitoring tool development
  • Case study: identifying developer oriented features and capabilities of API developer portals
  • Documenting software architecture design decisions in continuous software development – a multivocal literature review
  • Elinikäinen oppiminen ohjelmistotuotannon ammattilaisen keskeisenä
  • Miten huoltovarmuus toteutuu Ylen verkkouutisissa?
  • Utilizing Clustering to Create New Industrial Classifications of Finnish Businesses: Design Science Approach
  • Smoke Testing Display Viewer 5
  • Modernizing usability and development with microservices
  • On the affect of psychological safety, team leader’s behaviour and team’s gender diversity on software team performance: A literature review
  • Lean software development and remote working during COVID-19 - a case study
  • Julkaisusyklin tihentämisen odotukset, haasteet ja ratkaisut
  • Software Development in the Fintech Industry: A Literature Review
  • Design of an automated pipeline to improve the process of cross-platform mobile building and deployment
  • Haasteet toimijamallin käytössä ohjelmistokehityksessä, systemaattinen kirjallisuuskatsaus
  • Light-weight method for detecting API breakages in microservice architectures
  • Kirjallisuuskatsaus ja tapaustutkimus API-hallinnasta mikropalveluarkkitehtuurissa
  • In-depth comparison of BDD testing frameworks for Java
  • Itseohjautuvan auton moraalikoneen kehittämisen haasteet
  • Towards secure software development at Neste - a case study
  • Etuuspohjaisen eläkejärjestelyn laskennan optimointi vakuutustenhallintajärjestelmässä
  • Internal software startup within a university – producing industry-ready graduates
  • Applying global software development approaches to building high-performing software teams
  • Systemaattinen kirjallisuuskatsaus lääkinnällisistä ohjelmistoista ja ketterästä ohjelmistokehityksestä
  • Matalan kynnyksen ohjelmointialustan hyödyntäminen projektinhalinnassa
  • Uncertainty Estimation with Calibrated Confidence Scores
  • Tool for grouping test log failures using string similarity algorithms
  • Design, Implementation, and Validation of a Uniform Control Interface for Drawing Robots with ROS2
  • Assuring Model Documentation in Continuous Machine Learning System Development
  • Verkkopalvelun saavutettavuuden arviointi ja kehittäminen ohjelmistotuoteyrityksessä
  • Methods for API Governance automation: managing interfaces in a microservice system
  • Improving Web Performance by Optimizing Cascading Style Sheets (CSS): Literature Review and Empirical Findings
  • Implementing continuous delivery for legacy software
  • Using ISO/IEC 29110 to Improve Software Testing in an Agile VSE
  • An Open-Source and Portable MLOps Pipeline for Continuous Training and Continuous Deployment
  • System-level testing with microservice architecture
  • Green in software engineering: tools, methods and practices for reducing the environmental impacts of software use – a literature review
  • Machine Learning Monitoring and Maintenance: A Multivocal Literature Review
  • Green in Software Engineering: A Systematic Literature Review
  • Comparison of Two Open Source Feature Stores for Explainable Machine Learning
  • Open-source tools for automatic generation of game content
  • Verkkosovelluskehysten energiankulutus: vertaileva tutkimus Blazor WebAssembly ja JavaScript
  • Infrastruktuuri koodina -toimintatavan tehostaminen
  • Geospatial DBSCAN Hyperparameter Optimization with a Novel Genetic Algorithm Method
  • Hybrid mobile development using Ionic framework
  • Correlation of Unit Test Code Coverage with Software Quality
  • Factors affecting productivity of software development teams and individual developers: A systematic literature review
  • Case study: Performance of JavaScript on server side
  • Reducing complexity of microservices with API-Saga
  • Organizing software architecture work in a multi-team, multi-project, agile environment
  • Cloud-based visual programming BIM design workflow
  • IT SIAM toimintojen kehitysprojekti
  • PhyloStreamer: A cloud focused application for integrating phylogenetic command-line tools into graphical interfaces
  • Evaluation of WebView Rendering Performance in the Context of React Native
  • A Thematic Review of Preventing Bias in Iterative AI Software Development
  • Adopting Machine Learning Pipeline in Existing Environment

Current topic areas of interest to the research group (see below for the details)

Open source-related topic areas in collaboration with daimler truck.

  • Open Chain: Developing the Journey to Open Chain Compliance at the example of Daimler Truck
  • How should an industrial company (for example, Daimler Truck) leverage open source software: Building a framework with different dimensions, from efficient governance to value in inner source and open source projects
  • How can an organization efficiently incentivize inner-source activities? (on different levels, culture, infrastructure, governance, regulations & commitments.)
  • How can an industrial organization leverage value from actively engaging in FOSS activities (especially on active creation and contribution)
  • How can spillovers help Industrial companies to educate the rare resources but also attract and retain talent? Ref: Gandal, N., Naftaliev, P., & Stettner, U. (2017). Following the code: spillovers and knowledge transfer. Review of Network Economics , 16 (3), 243-267. Abstract: Knowledge spillovers in Open Source Software (OSS) can occur via two channels: In the first channel, programmers take knowledge and experience gained from one OSS project they work on and employ it in another OSS project they work on. In the second channel, programmers reuse software code by taking code from an OSS project and employing it in another. We develop a methodology to measure software reuse in a large OSS network at the micro level and show that projects that reuse code from other projects have higher success. We also demonstrate knowledge spillovers from projects connected via common programmers.

If interested, contact Tomi Männistö for further information

Hybrid software development (TOPIC AREA)

The current pandemic has brought many, even radical, changes to almost all software companies and software development organizations. Especially the sudden moves to working from home (WFH) in March 2020 forced them to adapt and even rethink many software engineering practices in order to continue productive software development under the new constraints.

Now (December 2021), various hybrid ways of working appear to become the new "normal" for the software industry in general. For instance, many companies are offering flexible workplace arrangements (WFX).

This thesis theme aims to explore and possibly explain such changes in contemporary software engineering. Potential research questions include the following:

  • How has the COVID-19 pandemic affected different software engineering activities (negatively or positively)? What are the mechanisms?
  • What adaptations and countermeasures have different software organizations devised to cope with the challenges?
  • What could be learned from them for future hybrid software development processes, practices and tools?

Contact: Petri Kettunen

MLOps -- as a derivative of DevOps -- is about practice and tools for ML-based systems that technically enable iterative software engineering practice. We have several funded positions in the area of MLOps in our research projects (IMLE4 https://itea4.org/project/iml4e.html and AIGA https://ai-governance.eu/ ) that can be tailored to the interest of the applicant. For details, contact Mikko Raatikainen ( [email protected] ).

Digital Twin of Yourself

Digital twins are virtual world dynamic models of real-world physical objects. They originate from manufacturing domains. In such environments, they are utilized, for example, for predictive maintenance of equipment based on real-time machine data.

Recently the application domains of digital twins have broadened to cover living objects – especially human beings, for instance, in medical domains (so-called Human Digital Twins). In this thesis topic, the objective is to design a digital twin of yourself. The choice of the digital twin dynamic model is free, and so are the data inputs. One possibility could be, for instance, your real-life physical exercise data (e.g., from a heart-rate monitor). You could also consider your Citizen Digital Twin, following your study data and yourself as a lifelong learner.

Software engineering and climate change (TOPIC AREA)

Global climate change may have various impacts on future software engineering on the one hand, and software engineering may affect climate change directly or indirectly, positively or negatively on the other hand. All that opens up many potentially important research problems. Specific theses in this topic area could be, for instance, the following themes:

  • Green IT (e.g., engineering new software with energy-efficiency requirements in order to reduce or limit power consumption and consequently the carbon footprint)
  • Carbon neutrality goals of software companies (e.g., software development organizations decreasing physical travelling in order to reduce their greenhouse gas emissions)
  • Developing software products or services for measuring climate change-related factors

The thesis could be a literature review, an empirical case study or a scientific design work.

Life-long learning for the modern software engineering profession

Specific intended learning outcomes for computer science (software engineering) graduates are life-long learning skills. Such skills and capabilities are essential in modern industrial software engineering environments. Workplace learning is a vital part of most professional software development jobs. What are the necessary life-long learning skills exactly? Why are those skills and capabilities essential in different software organizations? How can they be learned and improved? How do software professionals learn in their workplaces? What particular skills will be more critical in the future? Why? This topic could be investigated by case studies in real-life software organizations. The specific research questions could be some of the above or possibly focused on particular skills (e.g., assessing one's own and the works of other software developers). Contact: Petri Kettunen

Software development in non-ICT contexts (TOPIC AREA)

Software technology is increasingly applied in non-ICT domains and environments (e.g., healthcare, financial sector, telecommunications systems, industrial automation). Such conditions bring up many considerations for effective and efficient software engineering, such as: What are the key characteristics of different use domains (e.g., complexity, reliability)? What is the scope of the particular software system? How are the software requirements engineered? What are the specific constraints (e.g., regulations) in different domains to be considered in software engineering? How to measure the success of software projects and products? What software development methods (e.g., agile) are applicable in different domains? Why/why not? What particular software-related competencies are needed (e.g., digitalization, IoT, cyber-physical systems)? This research problem could be investigated theoretically (literature study) and empirically in industrial case studies. The actual research questions could be some of the above or formulated individually. Contact: Petri Kettunen

Creatively self-adaptive software architectures (TOPIC AREA)

We have recently started exciting research in the intersection between the research fields of self-adaptive software and computational creativity, intending to develop novel software architectures that can creatively adapt themselves in unforeseen situations. This initiative is a new research collaboration between the Discovery Group of Prof. Hannu Toivonen and ESE. There are different options for thesis work with either of the groups. To get a better idea of the topic, see Linkola et al. 2017. Aspects of Self-awareness: An Anatomy of Metacreative Systems. http://computationalcreativity.net/iccc2017/ICCC_17_accepted_submissions/ICCC-1… Contact: Tomi Männistö

Continuous Experimentation (TOPIC AREA)

Software product and service companies need capabilities to evaluate their development decisions and customer and user value. Continuous experimentation, as an experiment-driven development approach, may reduce such development risks by iteratively testing product and service assumptions critical to the software's success. Experiment-driven development has been a crucial component of software development, especially in the last decade. Companies such as Microsoft, Facebook, Google, Amazon and many others often conduct experiments to base their development decisions on data collected from field usage.  Contact: Tomi Männistö

Digitalization and digital transformations: impacts on software engineering and systems development (TOPIC AREA)

Digitalization is nowadays cross-cutting and inherent in most areas of businesses and organizations. Software is increasingly built-in and ubiquitous. Such trends and developments bring up many potential software research problems, such as: What does digitalization entail in different contexts? How should digitalization be taken into account in software development processes? What is the role of customer/user involvement in software-intensive systems development (e.g., digital services)? What are the key quality attributes? What new software engineering skills and competencies may be needed? What is the role of software (and IT) in general in different digital transformations (e.g., vs business process development)? How is digitalization related to traditional software engineering and computer science disciplines in different contexts? What aspects of software development and digital technologies are fundamentally new or different from the past? This research problem could be investigated theoretically (literature study) or empirically in industrial case studies. The actual research questions could be some of the above or formulated individually. Contact: Petri Kettunen

High-performing software teams (TOPIC AREA)

How is (high) performance defined and measured in software development (e.g., productivity)? Which factors affect it - positively or negatively - and how strongly (e.g., development tools, team composition)? Can we "build" high-performing software teams systematically, or do they merely emerge under certain favourable conditions? What are suitable organizational designs and environments for hosting and supporting such teams? See this link and this link for more info. Contact: Petri Kettunen

Software innovation (TOPIC AREA)

How are innovation and creativity taken into account in software development processes and methods (e.g., Agile)? What role do customer/user input and feedback play in software(-intensive) product creation (e.g., open innovation)? How to define and measure 'innovativeness' in software development? What makes software development organizations (more) innovative? See here for more about the topic. How can Open Data Software help innovation? Contact: Petri Kettunen

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Digital Commons @ USF > College of Engineering > Computer Science and Engineering > Theses and Dissertations

Computer Science and Engineering Theses and Dissertations

Theses/dissertations from 2023 2023.

Refining the Machine Learning Pipeline for US-based Public Transit Systems , Jennifer Adorno

Insect Classification and Explainability from Image Data via Deep Learning Techniques , Tanvir Hossain Bhuiyan

Brain-Inspired Spatio-Temporal Learning with Application to Robotics , Thiago André Ferreira Medeiros

Evaluating Methods for Improving DNN Robustness Against Adversarial Attacks , Laureano Griffin

Analyzing Multi-Robot Leader-Follower Formations in Obstacle-Laden Environments , Zachary J. Hinnen

Secure Lightweight Cryptographic Hardware Constructions for Deeply Embedded Systems , Jasmin Kaur

A Psychometric Analysis of Natural Language Inference Using Transformer Language Models , Antonio Laverghetta Jr.

Graph Analysis on Social Networks , Shen Lu

Deep Learning-based Automatic Stereology for High- and Low-magnification Images , Hunter Morera

Deciphering Trends and Tactics: Data-driven Techniques for Forecasting Information Spread and Detecting Coordinated Campaigns in Social Media , Kin Wai Ng Lugo

Automated Approaches to Enable Innovative Civic Applications from Citizen Generated Imagery , Hye Seon Yi

Theses/Dissertations from 2022 2022

Towards High Performing and Reliable Deep Convolutional Neural Network Models for Typically Limited Medical Imaging Datasets , Kaoutar Ben Ahmed

Task Progress Assessment and Monitoring Using Self-Supervised Learning , Sainath Reddy Bobbala

Towards More Task-Generalized and Explainable AI Through Psychometrics , Alec Braynen

A Multiple Input Multiple Output Framework for the Automatic Optical Fractionator-based Cell Counting in Z-Stacks Using Deep Learning , Palak Dave

On the Reliability of Wearable Sensors for Assessing Movement Disorder-Related Gait Quality and Imbalance: A Case Study of Multiple Sclerosis , Steven Díaz Hernández

Securing Critical Cyber Infrastructures and Functionalities via Machine Learning Empowered Strategies , Tao Hou

Social Media Time Series Forecasting and User-Level Activity Prediction with Gradient Boosting, Deep Learning, and Data Augmentation , Fred Mubang

A Study of Deep Learning Silhouette Extractors for Gait Recognition , Sneha Oladhri

Analyzing Decision-making in Robot Soccer for Attacking Behaviors , Justin Rodney

Generative Spatio-Temporal and Multimodal Analysis of Neonatal Pain , Md Sirajus Salekin

Secure Hardware Constructions for Fault Detection of Lattice-based Post-quantum Cryptosystems , Ausmita Sarker

Adaptive Multi-scale Place Cell Representations and Replay for Spatial Navigation and Learning in Autonomous Robots , Pablo Scleidorovich

Predicting the Number of Objects in a Robotic Grasp , Utkarsh Tamrakar

Humanoid Robot Motion Control for Ramps and Stairs , Tommy Truong

Preventing Variadic Function Attacks Through Argument Width Counting , Brennan Ward

Theses/Dissertations from 2021 2021

Knowledge Extraction and Inference Based on Visual Understanding of Cooking Contents , Ahmad Babaeian Babaeian Jelodar

Efficient Post-Quantum and Compact Cryptographic Constructions for the Internet of Things , Rouzbeh Behnia

Efficient Hardware Constructions for Error Detection of Post-Quantum Cryptographic Schemes , Alvaro Cintas Canto

Using Hyper-Dimensional Spanning Trees to Improve Structure Preservation During Dimensionality Reduction , Curtis Thomas Davis

Design, Deployment, and Validation of Computer Vision Techniques for Societal Scale Applications , Arup Kanti Dey

AffectiveTDA: Using Topological Data Analysis to Improve Analysis and Explainability in Affective Computing , Hamza Elhamdadi

Automatic Detection of Vehicles in Satellite Images for Economic Monitoring , Cole Hill

Analysis of Contextual Emotions Using Multimodal Data , Saurabh Hinduja

Data-driven Studies on Social Networks: Privacy and Simulation , Yasanka Sameera Horawalavithana

Automated Identification of Stages in Gonotrophic Cycle of Mosquitoes Using Computer Vision Techniques , Sherzod Kariev

Exploring the Use of Neural Transformers for Psycholinguistics , Antonio Laverghetta Jr.

Secure VLSI Hardware Design Against Intellectual Property (IP) Theft and Cryptographic Vulnerabilities , Matthew Dean Lewandowski

Turkic Interlingua: A Case Study of Machine Translation in Low-resource Languages , Jamshidbek Mirzakhalov

Automated Wound Segmentation and Dimension Measurement Using RGB-D Image , Chih-Yun Pai

Constructing Frameworks for Task-Optimized Visualizations , Ghulam Jilani Abdul Rahim Quadri

Trilateration-Based Localization in Known Environments with Object Detection , Valeria M. Salas Pacheco

Recognizing Patterns from Vital Signs Using Spectrograms , Sidharth Srivatsav Sribhashyam

Recognizing Emotion in the Wild Using Multimodal Data , Shivam Srivastava

A Modular Framework for Multi-Rotor Unmanned Aerial Vehicles for Military Operations , Dante Tezza

Human-centered Cybersecurity Research — Anthropological Findings from Two Longitudinal Studies , Anwesh Tuladhar

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy , Troi André Williams

Human-centric Cybersecurity Research: From Trapping the Bad Guys to Helping the Good Ones , Armin Ziaie Tabari

Theses/Dissertations from 2020 2020

Classifying Emotions with EEG and Peripheral Physiological Data Using 1D Convolutional Long Short-Term Memory Neural Network , Rupal Agarwal

Keyless Anti-Jamming Communication via Randomized DSSS , Ahmad Alagil

Active Deep Learning Method to Automate Unbiased Stereology Cell Counting , Saeed Alahmari

Composition of Atomic-Obligation Security Policies , Yan Cao Albright

Action Recognition Using the Motion Taxonomy , Maxat Alibayev

Sentiment Analysis in Peer Review , Zachariah J. Beasley

Spatial Heterogeneity Utilization in CT Images for Lung Nodule Classication , Dmitrii Cherezov

Feature Selection Via Random Subsets Of Uncorrelated Features , Long Kim Dang

Unifying Security Policy Enforcement: Theory and Practice , Shamaria Engram

PsiDB: A Framework for Batched Query Processing and Optimization , Mehrad Eslami

Composition of Atomic-Obligation Security Policies , Danielle Ferguson

Algorithms To Profile Driver Behavior From Zero-permission Embedded Sensors , Bharti Goel

The Efficiency and Accuracy of YOLO for Neonate Face Detection in the Clinical Setting , Jacqueline Hausmann

Beyond the Hype: Challenges of Neural Networks as Applied to Social Networks , Anthony Hernandez

Privacy-Preserving and Functional Information Systems , Thang Hoang

Managing Off-Grid Power Use for Solar Fueled Residences with Smart Appliances, Prices-to-Devices and IoT , Donnelle L. January

Novel Bit-Sliced In-Memory Computing Based VLSI Architecture for Fast Sobel Edge Detection in IoT Edge Devices , Rajeev Joshi

Edge Computing for Deep Learning-Based Distributed Real-time Object Detection on IoT Constrained Platforms at Low Frame Rate , Lakshmikavya Kalyanam

Establishing Topological Data Analysis: A Comparison of Visualization Techniques , Tanmay J. Kotha

Machine Learning for the Internet of Things: Applications, Implementation, and Security , Vishalini Laguduva Ramnath

System Support of Concurrent Database Query Processing on a GPU , Hao Li

Deep Learning Predictive Modeling with Data Challenges (Small, Big, or Imbalanced) , Renhao Liu

Countermeasures Against Various Network Attacks Using Machine Learning Methods , Yi Li

Towards Safe Power Oversubscription and Energy Efficiency of Data Centers , Sulav Malla

Design of Support Measures for Counting Frequent Patterns in Graphs , Jinghan Meng

Automating the Classification of Mosquito Specimens Using Image Processing Techniques , Mona Minakshi

Models of Secure Software Enforcement and Development , Hernan M. Palombo

Functional Object-Oriented Network: A Knowledge Representation for Service Robotics , David Andrés Paulius Ramos

Lung Nodule Malignancy Prediction from Computed Tomography Images Using Deep Learning , Rahul Paul

Algorithms and Framework for Computing 2-body Statistics on Graphics Processing Units , Napath Pitaksirianan

Efficient Viewshed Computation Algorithms On GPUs and CPUs , Faisal F. Qarah

Relational Joins on GPUs for In-Memory Database Query Processing , Ran Rui

Micro-architectural Countermeasures for Control Flow and Misspeculation Based Software Attacks , Love Kumar Sah

Efficient Forward-Secure and Compact Signatures for the Internet of Things (IoT) , Efe Ulas Akay Seyitoglu

Detecting Symptoms of Chronic Obstructive Pulmonary Disease and Congestive Heart Failure via Cough and Wheezing Sounds Using Smart-Phones and Machine Learning , Anthony Windmon

Toward Culturally Relevant Emotion Detection Using Physiological Signals , Khadija Zanna

Theses/Dissertations from 2019 2019

Beyond Labels and Captions: Contextualizing Grounded Semantics for Explainable Visual Interpretation , Sathyanarayanan Narasimhan Aakur

Empirical Analysis of a Cybersecurity Scoring System , Jaleel Ahmed

Phenomena of Social Dynamics in Online Games , Essa Alhazmi

A Machine Learning Approach to Predicting Community Engagement on Social Media During Disasters , Adel Alshehri

Interactive Fitness Domains in Competitive Coevolutionary Algorithm , ATM Golam Bari

Measuring Influence Across Social Media Platforms: Empirical Analysis Using Symbolic Transfer Entropy , Abhishek Bhattacharjee

A Communication-Centric Framework for Post-Silicon System-on-chip Integration Debug , Yuting Cao

Authentication and SQL-Injection Prevention Techniques in Web Applications , Cagri Cetin

Multimodal Emotion Recognition Using 3D Facial Landmarks, Action Units, and Physiological Data , Diego Fabiano

Robotic Motion Generation by Using Spatial-Temporal Patterns from Human Demonstrations , Yongqiang Huang

A GPU-Based Framework for Parallel Spatial Indexing and Query Processing , Zhila Nouri Lewis

A Flexible, Natural Deduction, Automated Reasoner for Quick Deployment of Non-Classical Logic , Trisha Mukhopadhyay

An Efficient Run-time CFI Check for Embedded Processors to Detect and Prevent Control Flow Based Attacks , Srivarsha Polnati

Force Feedback and Intelligent Workspace Selection for Legged Locomotion Over Uneven Terrain , John Rippetoe

Detecting Digitally Forged Faces in Online Videos , Neilesh Sambhu

Malicious Manipulation in Service-Oriented Network, Software, and Mobile Systems: Threats and Defenses , Dakun Shen

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Top 10 Software Engineer Research Topics for 2024

Home Blog Programming Top 10 Software Engineer Research Topics for 2024

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Software engineering, in general, is a dynamic and rapidly changing field that demands a thorough understanding of concepts related to programming, computer science, and mathematics. As software systems become more complicated in the future, software developers must stay updated on industry innovations and the latest trends. Working on software engineering research topics is an important part of staying relevant in the field of software engineering. 

Software engineers can do research to learn about new technologies, approaches, and strategies for developing and maintaining complex software systems. Software engineers can conduct research on a wide range of topics. Software engineering research is also vital for increasing the functionality, security, and dependability of software systems. Going for the Top Programming Certification course contributes to the advancement of the field's state of the art and assures that software engineers can continue to build high-quality, effective software systems.

What are Software Engineer Research Topics?

Software engineer research topics are areas of exploration and study in the rapidly evolving field of software engineering. These research topics include various software development approaches, quality of software, testing of software, maintenance of software, security measures for software, machine learning models in software engineering, DevOps, and architecture of software. Each of these software engineer research topics has distinct problems and opportunities for software engineers to investigate and make major contributions to the field. In short, research topics for software engineering provide possibilities for software engineers to investigate new technologies, approaches, and strategies for developing and managing complex software systems. 

For example, research on agile software development could identify the benefits and drawbacks of using agile methodology, as well as develop new techniques for effectively implementing agile practices. Software testing research may explore new testing procedures and tools, as well as assess the efficacy of existing ones. Software quality research may investigate the elements that influence software quality and develop approaches for enhancing software system quality and minimizing the faults and errors. Software metrics are quantitative measures that are used to assess the quality, maintainability, and performance of software. 

The research papers on software engineering topics in this specific area could identify novel measures for evaluating software systems or techniques for using metrics to improve the quality of software. The practice of integrating code changes into a common repository and pushing code changes to production in small, periodic batches is known as continuous integration and deployment (CI/CD). This research could investigate the best practices for establishing CI/CD or developing tools and approaches for automating the entire CI/CD process.

Top Software Engineer Research Topics

1. artificial intelligence and software engineering.

Intersections between AI and SE

The creation of AI-powered software engineering tools is one potential research area at the intersection of artificial intelligence (AI) and software engineering. These technologies use AI techniques that include machine learning, natural language processing, and computer vision to help software engineers with a variety of tasks throughout the software development lifecycle. An AI-powered code review tool, for example, may automatically discover potential flaws or security vulnerabilities in code, saving developers a lot of time and lowering the chance of human error. Similarly, an AI-powered testing tool might build test cases and analyze test results automatically to discover areas for improvement. 

Furthermore, AI-powered project management tools may aid in the planning and scheduling of projects, resource allocation, and risk management in the project. AI can also be utilized in software maintenance duties such as automatically discovering and correcting defects or providing code refactoring solutions. However, the development of such tools presents significant technical and ethical challenges, such as the necessity of large amounts of high-quality data, the risk of bias present in AI algorithms, and the possibility of AI replacing human jobs. Continuous study in this area is therefore required to ensure that AI-powered software engineering tools are successful, fair, and responsible.

Knowledge-based Software Engineering

Another study area that overlaps with AI and software engineering is knowledge-based software engineering (KBSE). KBSE entails creating software systems capable of reasoning about knowledge and applying that knowledge to enhance software development processes. The development of knowledge-based systems that can help software engineers in detecting and addressing complicated problems is one example of KBSE in action. To capture domain-specific knowledge, these systems use knowledge representation techniques such as ontologies, and reasoning algorithms such as logic programming or rule-based systems to derive new knowledge from already existing data. 

KBSE can be utilized in the context of AI and software engineering to create intelligent systems capable of learning from past experiences and applying that information to improvise future software development processes. A KBSE system, for example, may be used to generate code based on previous code samples or to recommend code snippets depending on the requirements of a project. Furthermore, KBSE systems could be used to improve the precision and efficiency of software testing and debugging by identifying and prioritizing bugs using knowledge-based techniques. As a result, continued research in this area is critical to ensuring that AI-powered software engineering tools are productive, fair, and responsible.

2. Natural Language Processing

Multimodality

Multimodality in Natural Language Processing (NLP) is one of the appealing research ideas for software engineering at the nexus of computer vision, speech recognition, and NLP. The ability of machines to comprehend and generate language from many modalities, such as text, speech, pictures, and video, is referred to as multimodal NLP. The goal of multimodal NLP is to develop systems that can learn from and interpret human communication across several modalities, allowing them to engage with humans in more organic and intuitive ways. 

The building of conversational agents or chatbots that can understand and create responses using several modalities is one example of multimodal NLP in action. These agents can analyze text input, voice input, and visual clues to provide more precise and relevant responses, allowing users to have a more natural and seamless conversational experience. Furthermore, multimodal NLP can be used to enhance language translation systems, allowing them to more accurately and effectively translate text, speech, and visual content.

The development of multimodal NLP systems must take efficiency into account. as multimodal NLP systems require significant computing power to process and integrate information from multiple modalities, optimizing their efficiency is critical to ensuring that they can operate in real-time and provide users with accurate and timely responses. Developing algorithms that can efficiently evaluate and integrate input from several modalities is one method for improving the efficiency of multimodal NLP systems. 

Overall, efficiency is a critical factor in the design of multimodal NLP systems. Researchers can increase the speed, precision, and scalability of these systems by inventing efficient algorithms, pre-processing approaches, and hardware architectures, allowing them to run successfully and offer real-time replies to consumers. Software Engineering training will help you level up your career and gear up to land you a job in the top product companies as a skilled Software Engineer. 

3. Applications of Data Mining in Software Engineering

Mining Software Engineering Data

The mining of software engineering data is one of the significant research paper topics for software engineering, involving the application of data mining techniques to extract insights from enormous datasets that are generated during software development processes. The purpose of mining software engineering data is to uncover patterns, trends, and various relationships that can inform software development practices, increase software product quality, and improve software development process efficiency. 

Mining software engineering data, despite its potential benefits, has various obstacles, including the quality of data, scalability, and privacy of data. Continuous research in this area is required to develop more effective data mining techniques and tools, as well as methods for ensuring data privacy and security, to address these challenges. By tackling these issues, mining software engineering data can continue to promote many positive aspects in software development practices and the overall quality of product.

Clustering and Text Mining

Clustering is a data mining approach that is used to group comparable items or data points based on their features or characteristics. Clustering can be used to detect patterns and correlations between different components of software, such as classes, methods, and modules, in the context of software engineering data. 

On the other hand, text mining is a method of data mining that is used to extract valuable information from unstructured text data such as software manuals, code comments, and bug reports. Text mining can be applied in the context of software engineering data to find patterns and trends in software development processes

4. Data Modeling

Data modeling is an important area of research paper topics in software engineering study, especially in the context of the design of databases and their management. It involves developing a conceptual model of the data that a system will need to store, organize, and manage, as well as establishing the relationships between various data pieces. One important goal of data modeling in software engineering research is to make sure that the database schema precisely matches the system's and its users' requirements. Working closely with stakeholders to understand their needs and identify the data items that are most essential to them is necessary.

5. Verification and Validation

Verification and validation are significant research project ideas for software engineering research because they help us to ensure that software systems are correctly built and suit the needs of their users. While most of the time, these terms are frequently used interchangeably, they refer to distinct stages of the software development process. The process of ensuring that a software system fits its specifications and needs is referred to as verification. This involves testing the system to confirm that it behaves as planned and satisfies the functional and performance specifications. In contrast, validation is the process of ensuring that a software system fulfils the needs of its users and stakeholders. 

This includes ensuring that the system serves its intended function and meets the requirements of its users. Verification and validation are key components of the software development process in software engineering research. Researchers can help to improve the functionality and dependability of software systems, minimize the chance of faults and mistakes, and ultimately develop better software products for their consumers by verifying that software systems are designed correctly and that they satisfy the needs of their users.

6. Software Project Management

Software project management is an important component of software engineering research because it comprises the planning, organization, and control of resources and activities to guarantee that software projects are finished on time, within budget, and to the needed quality standards. One of the key purposes of software project management in research is to guarantee that the project's stakeholders, such as users, clients, and sponsors, are satisfied with their needs. This includes defining the project's requirements, scope, and goals, as well as identifying potential risks and restrictions to the project's success.

7. Software Quality

The quality of a software product is defined as how well it fits in with its criteria, how well it performs its intended functions, and meets the needs of its consumers. It includes features such as dependability, usability, maintainability, effectiveness, and security, among others. Software quality is a prominent and essential research topic in software engineering. Researchers are working to provide methodologies, strategies, and tools for evaluating and improving software quality, as well as forecasting and preventing software faults and defects. Overall, software quality research is a large and interdisciplinary field that combines computer science, engineering, and statistics. Its mission is to increase the reliability, accessibility, and overall quality of software products and systems, thereby benefiting both software developers and end consumers.

8. Ontology

Ontology is a formal specification of a conception of a domain used in computer science to allow knowledge sharing and reuse. Ontology is a popular and essential area of study in the context of software engineering research. The construction of ontologies for specific domains or application areas could be a research topic in ontology for software engineering. For example, a researcher may create an ontology for the field of e-commerce to give common knowledge and terminology to software developers as well as stakeholders in that domain. The integration of several ontologies is another intriguing study topic in ontology for software engineering. As the number of ontologies generated for various domains and applications grows, there is an increasing need to integrate them in order to enable interoperability and reuse.

9. Software Models

In general, a software model acts as an abstract representation of a software system or its components. Software models can be used to help software developers, different stakeholders, and users communicate more effectively, as well as to properly evaluate, design, test, and maintain software systems. The development and evaluation of modeling languages and notations is one research example connected to software models. Researchers, for example, may evaluate the usefulness and efficiency of various modeling languages, such as UML or BPMN, for various software development activities or domains. 

Researchers could also look into using software models for software testing and verification. They may investigate how models might be used to produce test cases or to do model checking, a formal technique for ensuring the correctness of software systems. They may also examine the use of models for monitoring at runtime and software system adaptation.

The Software Development Life Cycle (SDLC) is a software engineering process for planning, designing, developing, testing, and deploying software systems. SDLC is an important research issue in software engineering since it is used to manage software projects and ensure the quality of the resultant software products by software developers and project managers. The development and evaluation of novel software development processes is one SDLC-related research topic. SDLC research also includes the creation and evaluation of different software project management tools and practices. 

Researchers may also check the implementation of SDLC in specific sectors or applications. They may, for example, investigate the use of SDLC in the development of systems that are more safety-critical, such as medical equipment or aviation systems, and develop new processes or tools to ensure the safety and reliability of these systems. They may also look into using SDLC to design software systems in new sectors like the Internet of Things or in blockchain technology.

Why is Software Engineering Required?

Software engineering is necessary because it gives a systematic way to developing, designing, and maintaining reliable, efficient, and scalable software. As software systems have become more complicated over time, software engineering has become a vital discipline to ensure that software is produced in a way that is fully compatible with end-user needs, reliable, and long-term maintainable.

When the cost of software development is considered, software engineering becomes even more important. Without a disciplined strategy, developing software can result in overinflated costs, delays, and a higher probability of errors that require costly adjustments later. Furthermore, software engineering can help reduce the long-term maintenance costs that occur by ensuring that software is designed to be easy to maintain and modify. This can save money in the long run by lowering the number of resources and time needed to make software changes as needed.

2. Scalability

Scalability is an essential factor in software development, especially for programs that have to manage enormous amounts of data or an increasing number of users. Software engineering provides a foundation for creating scalable software that can evolve over time. The capacity to deploy software to diverse contexts, such as cloud-based platforms or distributed systems, is another facet of scalability. Software engineering can assist in ensuring that software is built to be readily deployed and adjusted for various environments, resulting in increased flexibility and scalability.

3. Large Software

Developers can break down huge software systems into smaller, simpler parts using software engineering concepts, making the whole system easier to maintain. This can help to reduce the software's complexity and makes it easier to maintain the system over time. Furthermore, software engineering can aid in the development of large software systems in a modular fashion, with each module doing a specific function or set of functions. This makes it easier to push new features or functionality to the product without causing disruptions to the existing codebase.

4. Dynamic Nature

Developers can utilize software engineering techniques to create dynamic content that is modular and easily modifiable when user requirements change. This can enable adding new features or functionality to dynamic content easier without disturbing the existing codebase. Another factor to consider for dynamic content is security. Software engineering can assist in ensuring that dynamic content is generated in a secure manner that protects user data and information.

5. Better Quality Management

An organized method of quality management in software development is provided by software engineering. Developers may ensure that software is conceived, produced, and maintained in a way that fulfills quality requirements and provides value to users by adhering to software engineering principles. Requirement management is one component of quality management in software engineering. Testing and validation are another part of quality control in software engineering. Developers may verify that their software satisfies its requirements and is error-free by using an organized approach to testing.

In conclusion, the subject of software engineering provides a diverse set of research topics with the ability to progress the discipline while enhancing software development and maintenance procedures. This article has dived deep into various research topics in software engineering for masters and research topics for software engineering students such as software testing and validation, software security, artificial intelligence, Natural Language Processing, software project management, machine learning, Data Mining, etc. as research subjects. Software engineering researchers have an interesting chance to explore these and other research subjects and contribute to the development of creative solutions that can improve software quality, dependability, security, and scalability. 

Researchers may make important contributions to the area of software engineering and help tackle some of the most serious difficulties confronting software development and maintenance by staying updated with the latest research trends and technologies. As software grows more important in business and daily life, there is a greater demand for current research topics in software engineering into new software engineering processes and techniques. Software engineering researchers can assist in shaping the future of software creation and maintenance through their research, ensuring that software stays dependable, safe, reliable and efficient in an ever-changing technological context. KnowledgeHut’s top Programming certification course will help you leverage online programming courses from expert trainers.

Frequently Asked Questions (FAQs)

Ans: To find a research topic in software engineering, you can review recent papers and conference proceedings, talk to different experts in the field, and evaluate your own interests and experience. You can use a combination of these approaches. 

Ans: You should study software development processes, various programming languages and their frameworks, software testing and quality assurance, software architecture, various design patterns that are currently being used, and software project management as a software engineering student. 

Ans: Empirical research, experimental research, surveys, case studies, and literature reviews are all types of research in software engineering. Each sort of study has advantages and disadvantages, and the research method chosen is determined by the research objective, resources, and available data. 

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Eshaan is a Full Stack web developer skilled in MERN stack. He is a quick learner and has the ability to adapt quickly with respect to projects and technologies assigned to him. He has also worked previously on UI/UX web projects and delivered successfully. Eshaan has worked as an SDE Intern at Frazor for a span of 2 months. He has also worked as a Technical Blog Writer at KnowledgeHut upGrad writing articles on various technical topics.

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Home > Robinson College of Business > Computer Information Systems > CIS_DISS

Computer Information Systems Dissertations

Dissertations from 2023 2023.

Investigating the Effectiveness of Algorithmic Interventions in Health Decision Making , Jung min Lee

Dissertations from 2022 2022

Organizational Intelligence in Digital Innovation: Evidence from Georgia State University , Khaleed M. Fuad

The Impact of Corporate Engagement in Open-Source Enterprise Systems Community on Release Performance , Peiwei Li

Essays on IT and Platform Governance from External Stakeholder Perspectives , Junyoung Park

Deciding to Fail: Three Essays about Self-Interest in Systems , Pengcheng Wang

Investigating Decentralization, Incentives, and Configurations of Blockchain Governance , Rongen Zhang

Dissertations from 2021 2021

Decision-Making Dilemma in Human-Automation Interaction: Who Should Grasp Authority, Human or Intelligent Systems? , Xiaocong Cui

Empirical Essays on Crowd-based Digital Platforms and Product Innovation Performance , Heeseung Lee

Collective Attention Allocation for Innovation Productivity in Open-Source Software Projects: A Configurational Perspective , Yanran Liu

Network Effects and Decentralized Governance in Public Blockchain Ecosystems , Yukun Yang

Dissertations from 2020 2020

Managing Technical Debt in Agile Software Development Projects , Maheshwar Boodraj

Essays on Motivations and Motivational Affordances in the Context of Health Information Technology , Hyoungyong Choi

Technical and Behavioral Interventions for Medication Adherence through Mobile Health , Xinying Liu

Conversational AI Agents: Investigating AI-Specific Characteristics that Induce Anthropomorphism and Trust in Human-AI Interaction , Kambiz Saffarizadeh

Dissertations from 2019 2019

Explaining the Privacy Paradox through Identifying Boundary Conditions of the Relationship between Privacy Concerns and Disclosure Behaviors , Tawfiq Alashoor

Unravelling the Influence of Online Social Context on Consumer Health Information Technology (CHIT) Implementations , Amrita George

Essays on Technology in Presence of Globalization , Joshua Madden

Three Essays on Digital Innovation from an Intellectual Property Rights Perspective , Zhitao Yin

Dissertations from 2018 2018

A "Practice-Based" Theory of the Firm: A Practice Theory Perspective to Organizational Strategy Development and Knowledge Management , Sayed Mahdi Almohri

Extracting Business Value of IT and Identifying IT Innovation in Large Institutional Settings Undergoing Regulatory Change , Jessica Pye

Three Empirical Essays on Health Informatics and Analytics , Youyou Tao

Classification And Analysis Of Mobile Health Evaluation Through Taxonomy and Method Development , Alan T. Yang

Dissertations from 2017 2017

Integrating online-offline interactions to explain societal challenges , Christine Abdalla Mikhaeil

Dissertations from 2016 2016

Managing Enterprise Systems Post Implementation through Competency Centers: An Inquiry into Assemblage and Emergence , Arun Aryal

Essays on Health Information Technology: Insights from Analyses of Big Datasets , Langtao Chen

Three Essays on the Empowerment Role of Information Technology in Healthcare Services , Liwei Chen

Towards a Better Comprehension of Adaptation to Information and Communication Technologies: A Multi-level Approach , Najma Saidani

Smart Interventions for Effective Medication Adherence , Neetu Singh

Dissertations from 2015 2015

An Event-based Analysis Framework for Open Source Software Development Projects , Tianjie Deng

Affect and Decision Making in Troubled Information Technology Projects , Hyung Koo Lee

Risks, Controls and Business Value of IT-Enabled Interfirm and Intrafirm Processes , Chaitanya Sambhara

Dissertations from 2014 2014

Traveling of Requirements in the Development of Packaged Software: An Investigation of Work Design and Uncertainty , Thomas Gregory

Genres of Inquiry in Design Science Research: Applying Search Conference to Contemporary Information Systems Security Theory , Mala Kaul

The Role of Regret and Its Applications in IS Decision Making , EunHee Park

New Perspectives on Implementing Health Information Technology , Sumantra Sarkar

Dissertations from 2013 2013

An Investigation of the Relationships between Goals and Software Project Escalation: Insights from Goal Setting and Goal Orientation Theories , Jong Seok Lee

The Impact of IT-Enabled and Team Relational Coordination on Patient Satisfaction , Darryl S. Romanow

Dissertations from 2012 2012

Knowledge Worker Behavioral Responses and Job Outcomes in Mandatory Enterprise System Use Contexts , Robert Hornyak

The Management of Distance in Distributed-work , Chauvet Mathieu

Realizing Shared Services - A Punctuated Process Analysis of a Public IT Department , Tim Olsen

A Requirements-Based Exploration of Open-Source Software Development Projects – Towards a Natural Language Processing Software Analysis Framework , Radu Vlas

Dissertations from 2011 2011

Health Information Systems Affordances: How the Materiality of Information Technology Enables and Constrains the Work Practices of Clinicians , Chad Anderson

Towards Information Polycentricity Theory: Investigation of a Hospital Revenue Cycle , Rajendra Singh

Examining Scholarly Influence: A Study in Hirsch Metrics and Social Network Analysis , Hirotoshi Takeda

Dissertations from 2010 2010

What Support Does Information and Communication Technology (ICT) Offer to Organizational Improvisation During Crisis Response ? , Anouck Adrot

Quality in IS Research: Theory and Validation of Constructs for Service, Information, and System , Yi Ding

Effect of Digital Enablement of Business-to-Business Exchange on Customer Outcomes: The Role of Information Systems Quality and Relationship Characteristics , Stephen M. Du

How and Why do IT Professionals Leave their Salaried Employment to Start a Company? , Mourmant Gaetan

A Novel Approach to Ontology Management , Jong Woo Kim

Investigating the Relationship between IT and Organizations: A Research Trilogy , Benoit Raymond

The Role of Stakeholder Perceptions during IT-Enabled Change: An Investigation of Technology Frames of Reference in a Sales Process Innovation Project , Brett Young

Dissertations from 2009 2009

An Examination of the Deaf Effect Response to Bad News Reporting in Information Systems Projects , Michael John Cuellar

Exploring IT-Based Knowledge Sharing Practices: Representing Knowledge within and across Projects , Alina Maria Dulipovici

Studies on Adaptation to Information Systems: Multiple Roles and Coping Strategies , Christophe Elie-Dit-Cosaque

A User-Centered Perspective on Information Technologies in Museums , Jessie Pallud

Trusting IT Artifacts: How Trust Affects our Use of Technology , Anthony Osborn Vance

Controlling Telework: An Exploratory Investigation of Portfolios of Control Applied to Remote Knowledge Workers , Jijie Wang

A Multidimensional and Visual Exploration Approach to Project Portfolio Management , Guangzhi Zheng

Dissertations from 2008 2008

Digital Integration: Understanding the Concept and its Environmental Predictors , Ricardo M. Checchi

Managing the Tension between Standardization and Customization in IT-enabled Service Provisioning: A Sensemaking Perspective , Mark O. Lewis

Patient Monitoring via Mobile Ad Hoc Network: Power Management, Reliability, and Delays , Sweta Sneha

Dissertations from 2007 2007

A Contextualist Approach to Telehealth Innovations , Sunyoung Cho

Escalation of Commitment in Information Technology Projects: A Goal Setting Theory Perspective , Vijay Kasi

Generating User-centric Dynamic and Adaptable Knowledge Models for World Wide Web , Li Lei

Improving Practices in a Small Software Firm: An Ambidextrous Perspective , Nannette Napier

Bad News Reporting on Troubled IT Projects: The Role of Personal, Situational, and Organizational Factors , Chongwoo Park

Individual-Technology Fit: Matching Individual Characteristics and Features of Biometric Interface Technologies with Performance , Adriane Randolph

Dissertations from 2006 2006

A Study of the Quality of Service in Group Oriented Mobile Transactions , Punit Ahluwalia

Leverage Points for Addressing Digital Inequality: An Extended Theory of Planned Behavior Perspective , JJ Po-An Hsieh

Exploratory and Exploitative Knowledge Sharing in Interorganizational Relationships , Ghiyoung Im

Business Process Integration: A Socio-Cognitive Process Model and a Support System , Radhika Jain

Upgrading Packaged Software: An Exploratory Study of Decisions, Impacts, and Coping Strategies from the Perspectives of Stakeholders , Huoy Min Khoo

A Process to Reuse Experiences via Narratives Among Software Project Managers , Stacie Clark Petter

Dissertations from 2005 2005

New Perspectives on the System Usage Construct , Andrew Burton-Jones

Modeling Dynamics in Agile Software Development , Lan Cao

Reuse of Scenario Specifications Using an Automated Relational Learner , Han-Gyun Woo

Dissertations from 2004 2004

Access Anytime Anyplace: An Empircal Investigation of Patterns of Technology Use in Nomadic Computing Environments , Karlene C. Cousins

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Engineering Dissertation Topics – Selected Industry-Oriented Topics

Published by Owen Ingram at January 2nd, 2023 , Revised On August 18, 2023

Engineering is one of the most rewarding careers for students. With solid research, investigation and analysis, engineering students dig deep through different engineering ideas throughout the length of their degree programmes.

All undergraduate, Master and Phd engineering students must complete a dissertation on a topic that adds some value to their area of study.

Engineering is a branch of science that deals with the design and creation of products, machines, systems, and processes. Engineering students are responsible for the overall implementation of engineering projects, i.e., the invention of new products or services, the design of new products and systems, development of new processes, materials, or methods.

Here are some of the many responsibilities of an engineer.

  • Engineers design machines, buildings, and systems that help people do their jobs more quickly or efficiently.
  • They determine ways to make devices safer, faster, or more efficient.
  • Engineers create new technology to automate manual work and save time.

Engineering topics can be divided into different disciplines, such as civil, electrical, mechanical, and industrial. So without further delay, here are the engineering dissertation topics you have been looking for.

Engineering Dissertation Topics 

Civil engineering.

Civil engineers design and oversee construction projects such as roads, bridges, hospitals, water treatment plants, and airports.

Civil Engineering Dissertation Topics

The following list of civil engineering dissertation topics will help you with your next dissertation essay.

  • Bridges and Tunnels
  • Environment and Climate Change
  • Building Structure
  • Planning and management in the construction industry
  • Construction technology
  • Sustainable construction materials
  • Health, safety, and environment
  • Building information modelling (BIM)
  • Smart buildings
  • Construction management and project management
  • Sustainable design

Complete list of civil engineering dissertation topics

Electrical Engineering

Electrical engineers design and develop complex electrical machines, electronic devices, and power systems. They also use their skills to solve problems in robotics, medical technology, computer engineering, and other technologies.

Electrical Engineering Dissertation Topics

There are many research topics in Electrical Engineering. Some of them are listed below:

  • Electrical circuits and devices
  • Electrical systems, devices, and components
  • Electrical power engineering
  • Power electronics and power generation
  • Power transmission
  • Power distribution
  • Control and automation
  • Transmission systems
  • Signal processing and communications
  • Electronic engineering system design

How Can ResearchProspect Help?

ResearchProspect writers can send several custom topic ideas to your email address. Once you have chosen a topic that suits your needs and interests, you can order for our dissertation outline service which will include a brief introduction to the topic, research questions , literature review , methodology , expected results , and conclusion . The dissertation outline will enable you to review the quality of our work before placing the order for our full dissertation writing service!

Mechanical Engineering

Mechanical engineers design and develop engines, cars, aeroplanes, and other machinery used in factories. They also help manufacturers improve product quality by creating processes that increase efficiency while reducing costs.

Mechanical engineering covers a wide range of topics, from the materials used in the design and construction of products to the analysis of complex systems and processes. The field is diverse, but some of the many fields of topics may include.

Mechanical Engineering Dissertation Topics

The following list includes some of the most common topics in mechanical engineering:

  • Human factors and systems engineering
  • Design for manufacturing
  • Machine design and control
  • Manufacturing systems
  • Materials science, engineering, and technology
  • Manufacturing process technology, product design, and development
  • Engineered materials and structures
  • Materials processing, fabrication, and inspection technologies
  • Mechanics of materials (including solid mechanics)
  • Thermodynamics and heat transfer in engineering systems

Complete list of mechanical engineering dissertation topics. 

Industrial Engineering

Industrial engineers work with manufacturing companies to improve efficiency by redesigning processes. An example to see how products move through production lines or how workers perform their jobs more effectively.

Industrial Engineering Dissertation Topics

  • Sustainable development and its impact on the environment
  • Design of products and services to meet the needs of the consumer
  • Industrial safety and health management systems
  • Energy-efficient products, processes, and buildings
  • Sustainable production systems
  • Environmental Management System (EMS) for manufacturing industries
  • Intelligent materials, devices, and systems
  • Managing natural resources in an environmentally responsible way

View chemical engineering dissertation topics here. 

Computer Engineering

Computer engineers are concerned with all aspects of information technology, including hardware, software, and systems. Computer engineers analyze problems in computer science and apply their knowledge to design new processes and devices. They may specialize in areas such as artificial intelligence or embedded systems.

Computer Engineering Dissertation Topics

  • Designing a system to provide an automated control system for an aircraft
  • Computer organization, software engineering, and programming languages
  • Design of a computer-based neural network controller for use in controlling an aircraft
  • Creation of a computer program to simulate the operation of a molecule in a given chemical reaction
  • Development of a real-time software package for the control of complex industrial machines
  • Development of an intelligent software system for controlling large-scale industrial processes

Computer engineering dissertation topics complete list. 

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Metallurgy Engineering

Metallurgy engineers are involved in designing and constructing equipment to extract metals from ores. They also develop processes for treating the ores to recover valuable metals and other materials sold at high prices because of their growing demands. Moreover, metallurgical engineers may specialize in producing steel by smelting iron ore or coal into pig iron (a low-grade form of steel). They may also work with other types of scarce metals in a limited quantity under the earth’s crust, such as aluminum or titanium.

Metallurgy Engineering Dissertation Topics

  • The use of Nickel and Nickel Alloys in the Manufacturing Industry
  • The Effect of Processing Techniques on the Properties of Ferrous Metals
  • Corrosion Resistance of Stainless Steels
  • Corrosion Behavior and Corrosion Inhibiting Mechanisms in Ferrous Metals
  • Corrosion and Corrosion Resistance Control in Cast Iron and Steel Castings and Forgings
  • Corrosion Control in High-Strength Low-Alloy Steels by Selective Annealing
  • Corrosion Behavior in Stainless Steels Used for Structural Applications
  • Mechanical Properties of Ferrous Metallics by Thermal Treatment and Chemical Modification Methods

Needless to say, engineering is a diverse field with a pool of opportunities for those looking to build a career in this booming field. If you’re still wondering which engineering topice is best for you, the choice will depend on your interests and abilities.

Therefore, it’s best to take some time and explore different options before choosing a topic Hopefully, the above engineering dissertation topics will help you write an appealing dissertation for your final year.

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For engineering dissertation topics:

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  • Select a topic aligning with your passion and career goals.

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As a computer networking student, you have a variety of networking topics to choose from. With the field evolving with each passing day.

Here is a list of sports dissertation topics to help you choose the one studies any one as per your requirements.

Fintech, short for financial technology, is a rapidly growing industry that focuses on using technology to improve the efficiency of traditional banking and financial services.

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Engineering Dissertation Topics

A dissertation (or a final year project report) is a comprehensive technical report of the research work carried out. A dissertation must present some new, original concepts that lead to further research. The core area of a dissertation consists of a hypothesis (or a research question) upon which an investigation is conducted and, in most cases, inevitably leads to further research. A dissertation must be focused, concise and must address the research topics at every level. Also, along with research, a dissertation is expected to present complete evidence of research work in the form of research methods. Sometimes it’s hard to even know where to start. Herein, many engineering research areas, currently being sought after in the industry and academia, are suggested, including electronics, sensors technology, environmental engineering, supply chain engineering, computer science engineering, electrical engineering and civil engineering, to help you start your research.

  • Electronics and Communication Dissertation Topics

Sensors Technology Dissertation Topics

Environmental engineering dissertation topics, supply chain engineering dissertation topics, supply chain management dissertation topics, computer science engineering dissertation topics, electrical engineering dissertation topics, civil engineering dissertation topics, management related engineering dissertation topics, electronics and communications dissertation topics.

Over the past decade the rise of electronic communication has been revolutionised; it is the fastest growing technology. There are numerous areas of research in this field; however, the most demanding ones are highlighted below.

  • Defining the boundaries of electrical signals for current electronics (communication) systems.
  • The limitation of fibre optic communication systems and the possibility of further improving their efficiency.
  • Developing the embedded communication system for the national grid to optimise energy usage.
  • Improvement of inter-symbol interference in optical communications.
  • A study of the various forms of errors and the development of an equalisation technique to reduce the error rates in data.
  • Gaussian pulse analysis and the improvement of this pulse to reduce errors.
  • Realising the potential of RFID in the improvement of supply chain.
  • Radiation in integrated circuits and electronic devices.
  • Design of high speed communication circuits that effectively cut down signal noise.
  • Spectral sensing research for water monitoring applications and frontier science and technology for chemical, biological and radiological defence.
  • Nano-structured membranes for preparative purifications of biopharmaceuticals.

The rise of smart technology has been revolutionising sensor technologies, and there is a high demand to make more efficient and compact sensors. The following topics are a few areas that researchers are currently working in to realise further potentials.

  • Design and development of a pressure sensor for a solar thermal panel.
  • An investigation into wind speed and direction sensors to optimise the operations of wind turbines.
  • Utilising MEMS for profiling airflow around large building structures.
  • Development of micro sensors to measure oil flow rate in tanks.
  • Development and implementation of micro sensors to study pressure of the blood stream.
  • Development of sensors to measure heat generated from solar panels.
  • Sensing and controlling the intensity of light in LEDs.
  • Research and computational simulation of a natural olfactory biosensor.
  • Development of glucose biosensors using nanotechnology.

We are living in the age of technology where the driving force is to reduce the environmental impact of engineering products. Many countries have been undertaking projects supporting the environment and aiming to reduce carbon emissions. The following engineering dissertation topics are of utmost interest for researchers in the industry.

  • Analysing the impact of aviation industry on the environment and the potential ways to reduce it.
  • The environmental cost of the so called green energy, ‘wind energy’.
  • An analysis of factors that hinder the realising of cutting-edge technology for reducing carbon emissions from automobiles.
  • Design and development of a system for measuring the carbon index of an energy intensive company.
  • Process improvement techniques to identify and remove waste in the automotive industry.
  • Process mapping techniques to identify bottle necks for supply chain industry.
  • A study of compressor operations on a forging site and mapping operations to identify and remove energy waste.
  • Improving processes to reduce kWh usage and reduce inefficiencies.
  • Developing a compact device to measure energy use for a household.
  • In the forging industry how can changing burners within furnaces help organisations achieve energy efficiency?
  • How can gas consumption be reduced and efficiency introduced to reduce kWh usage?
  • How can voltage reduction devices help organisations achieve efficiency in electricity usage?
  • What are carbon credits and how can organisations generate them?
  • There are some organisations that use water excessively, with bills totalling more than £25,000. Identify the main reasons for such water usage and investigate better ways to introduce water efficiency and create savings.
  • Identify the ways by which efficient control systems using information systems can be introduced to study the energy usage in a machining factory.
  • A project to set up ways to measure natural gas flow ultrasonically and identify waste areas.
  • How can water conductivity probes help determine water quality and how can water be reused?

Supply chain plays an important role in the manufacturing business sector. It is important that the supply chain is well supported by efficient methods and processes. Your engineering dissertation topics could be about:

  • Highlighting the difference between the supply chain engineering and management for a company to improve output.
  • Analysing the key factors in process planning and optimisation of supply chain for a manufacturing company.
  • Developing a supply chain template for a small but thriving online business.
  • How can organisations achieve success by reducing bottlenecks in supply chain?
  • Just-in-time – is it really valid? Measurement of losses within just-in-time process implementation.
  • How can process efficiency be introduced to reduce waste within the manufacturing process?
  • Supplier relationship is an important factor for the success of just-in-time. How can organisations ensure successful transactions?
  • Research to identify efficient logistics operations within a supply chain.
  • Research to introduce efficiency within information systems and support timely transfer of knowledge and information.
  • The effect of globalisation on supply chain engineering/management for large multi-national companies.
  • Research studying the impact of culture on supply chain industries: identification of factors that generate inefficiencies with the supply chain.

Supply chain management involves the administration, management, control and supervision of the movement of goods and services from supplier to manufacturer to wholesaler to retailer and to the end consumer. Supply chain management involves coordinating and integrating these elements using an effective and efficient approach and methodology. Supply chain management is important for businesses to ensure there is minimum waste, drive innovation thereby creating integrated value chains. Supply chain management plays an important and central role in the success of a business. Please find a list of topics on supply chain management that may be useful for your engineering dissertation:

  • A detailed investigation into the need and use of dynamic staff to determine and rectify supply chain problems with a specific focus on the construction industry.
  • Research into eco-friendly and sustainable practices in supply chain management.
  • Research to develop a learning organisation and its impact on supply chain management.
  • Research to measure and develop intellectual capital within the supply chain industry.
  • A detailed study of innovative forecasting and demand planning strategies for supply chain management
  • Research study to create measurements to study the impact of learning organisation on performance measurement in supply chain industry
  • Impact of training on knowledge performance index within supply chain industry.
  • The behaviour of Carbon index with the implementation of a learning organisation.
  • Developing a framework for supply chain management in densely populated urban cities
  • Detailed investigation and analysis taking into account supply chain and logistical strategies for perishable goods.
  • The influence and impact of emerging e-commerce technologies on supply chain management.

Computer science engineering focuses on the key elements of computer programming and networking with a focus on gaining knowledge of the design, implementation and management of information systems. Information systems play a major role in computer science engineering and an integral component to the successful operations of organisations. The management of information technology systems is a major element for organisations. The following could be used for an engineering dissertation as well as a computing dissertation:

  • How can organisations ensure that information system is effectively used to maintain process efficiency?
  • How can learning organisations influence the development of information systems?
  • The role of risk management in information technology systems of organisations.
  • Research to identify and reduce e-waste using information technology strategies and systems.
  • Current status and research on E-waste in the United Kingdom
  • Development of measurement systems to measure e-waste.
  • A detailed review of the role of information technology in improving productivity and transforming organisations.
  • An investigation into the use of information technology as a tool for sustained competitive advantage.
  • A high-level investigation and detailed review into best practices for the implementation of information technology in modern day organisations.

Electrical engineering is focused on the design, development, testing, supervision and the manufacturing of electrical equipment. Electrical engineers design the electrical systems of automobiles, aircrafts, power generation equipment, communications systems, radar and navigational systems. The design and development of these electrical components are key and central to modern day life. There are several topics within this area that you could research for your electrical engineering dissertation:

  • Development of a system to study the efficiency of motors in order to reduce kWh usage
  • Setting up of a control system to monitor the process usage of compressors.
  • Develop a scheme to normalise compressor output to kWh.
  • Research to investigate, develop and introduce schemes to ensure efficient energy consumption by electrical machines.
  • Research to study transformer losses and reduce energy loss.
  • Research to study metering techniques to control and improve efficiency.
  • Research to introduce smart metering concepts to ensure efficient use of electricity.
  • Integration of smart metering pulsed outputs with wireless area networks and access real-time data.
  • Developing effective strategies and methodical systems for pay as you go charging for electric vehicles
  • A detailed review and investigation into the key issues and challenges facing rechargeable lithium batteries
  • Trends and challenges in electric vehicles technologies
  • Smart charging of electric vehicles on the motorway

The main emphasis of civil engineering in recent times is focused on sustainable development of quality, durable structures that deliver value for money, maximise the benefits from innovation and meets the specifications of the end users. Construction of sustainable houses has been a top priority within civil engineering. The following research topics are being actively undertaken and may be a good area for you to base your research on your own engineering dissertation:

  • Development of sustainable homes making use of renewable energy sources.
  • The use of sustainable materials for construction: design and delivery methods.
  • The role of environmental assessment tools in sustainable construction
  • The use of warm mix asphalt in road construction
  • Research to study properties of concrete to achieve sustainability.
  • Development of waste reduction strategy to achieve sustainable concepts
  • High-level review of the barriers and drivers for sustainable buildings in developing countries
  • Research to study the impact of sustainability concepts on organisational growth and development.
  • Sustainable technologies for the building construction industry
  • Building Information Modelling in the construction industry
  • Research regarding micromechanics of granular materials.
  • Research to study and develop water treatment processes.
  • Research to set up remote sensing applications to assist in the development of sustainable construction techniques.
  • High-level strategies, best practice guidelines and methodologies for sustainable construction.
  • State of the art practice for recycling in the construction industry.
  • Key factors and risk factors associated with the construction of high rise buildings.
  • An investigation into health and safety in the construction industry.

Engineering management is the application of the practice of management to the practice of engineering. Engineering management integrates problem-solving, engineering, technological developments and advancements in organizational structure, administrative, and planning abilities of management in order to oversee the operational performance of complex engineering driven enterprises. These two topics go hand in hand and support each other quite well. It is important that both sides are well balanced. The following research topics could be useful for your engineering dissertation:

  • Steps to conduct management of change to ensure smooth process improvement.
  • Research to sustainably manage a project team.
  • Research to study the management of engineering projects and various risks involved with them.
  • Research to identify process improvement plans to support business strategies.
  • Efficient supply chain management to ensure and develop key motivational skills within staff members.
  • How leadership can help efficiency within a learning organisation.
  • Developing an integrated approach to strategic management in organisations.
  • Creating and sustaining competitive advantage in engineering organisations.
  • Developing frameworks for sustainable assessments taking into account eco-engineering measures.
  • The role of engineers in managing development in emerging countries.

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Computer Science Dissertation Ideas for Master’s and UG Students

Computer science Dissertation Topics

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How to Pick a Computer Dissertation Idea?

Network and security dissertation topics, software and programming dissertation topics, information technology dissertation topics, forensic computing science dissertation ideas, chill all you want while experts create your computer dissertation.

Computer science students are exposed to various coding tasks and theories. Additionally, all of these are the subjects of their dissertation. These students squint so hard that their hair begins to fall out while they try to think of a topic or an idea. So, here are some intriguing, unique, yet straight forward cases suggested by professionals. Offering Computer Science dissertation ideas to get you started with writing and spare your hair and learning time.

Selecting a topic is the first step in the beginning of any academic project. It is especially true when writing for your dissertation, which requires you to follow several instructions. And be perfect with your Computer Science dissertation project ideas. No one can afford to make a mistake and have a dissertation rejected after ensuring the numerous factors that it includes.

1. Requirement

The first step is to review the dissertation's guidelines, which include things like word count, deadline, restrictions, and a given theme. These guidelines will assist you in deciding how far to pursue a topic choice. When it comes to this part, you should look for Computer Science dissertation examples to be doubly sure.

2. Statement

A thesis statement is a single phrase on which your entire task will be based. There are many available themes when a dissertation is offered. It would help to create an idea for yourself once you know its requirements. The best course of action would be for you to work on topic finalisation based on the same area.

3. Preexisting

Be clever as you research the subject for your dissertation. Compare your case to various examples of the same before. Having some Computer Science dissertation examples of prior content to draw inspiration from will significantly help. It will help you make intelligent adjustments and improve the reader-attractiveness of your title.

4. Research

When conducting exhaustive research for your dissertation, you must demonstrate your abilities. Similarly, thorough research is necessary when developing a title for it. Choosing relevant books and articles will assist you in selecting a stylish item. Make a list of the subjects you are interested in so you can reference them later in your essay.

5. Plausible

While understanding the guidelines, you must be aware of the deadline and any restrictions your academic assignment has. Will you have enough time, for instance, to finish the tasks and research related to your title? Whatever Computer Science dissertation topics you pick to fictionalise, make sure that it is doable in the time so that you can write your paper.

6. Approval

Most dissertations require you to submit an overview of your theme, topic, and thesis statement, which must first receive the approval of your professor and higher authority. Then talk to them about your plan to get their feedback on improving it. By taking this step, you can save time on a subject that might be rejected or, you can look for a better option by looking into some of the Computer Science dissertation example.

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Network and security is an area of computer science that will help you select the correct theme. Be clear about this field because you will have to present strong content in front of the professor to get your desired grades. Below are some of the most popular network and security Computer Science dissertation ideas for students.

  • There are possible privacy and security risks when using electronic ID cards for online authentication
  • How can the security of intelligent card network transmissions be increased and relay attacks prevented?
  • What security measures do IEEE 802.11-based WLANs employ?
  • How do you create a compelling 4G network intrusion detection system?
  • Consider using intrusion detection systems to analyse data intelligently across various gateways
  • How do I create a safe runtime programming environment to analyse the behaviour of malicious botnets and network worms?
  • A programmatic analysis of network security.
  • Which strategic and methodological approaches are used when developing ICT systems?
  • How can a distributed file-sharing system be createdand used to support content mobility and disconnection-tolerant communication?
  • How do I create a safe, expandable, and component-based network?
  • Hibernates and struts are used in the monitoring tool
  • Placement of scalable routers in software-defined networks
  • An evaluation framework for peer-to-peer (overlay) networks that are structured for secure routing
  • What problems do coordinated transmission methods in the upcoming 5G wireless networks face?
  • Studies on the effectiveness of VoIP over Ethernet and wireless LANs.
  • Using propagation measurements, what effect does signal strength have on the throughput of a Wi-Fi link?
  • Software-defined networking for detecting network traffic abnormalities
  • How can you protect data transfer over Wi-Fi and P2P networks?
  • How can database technologies be used to manage data on networks?
  • Redundancy and fault recovery for real-time wireless networking systems

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It is said if you are not satisfied with any other computer Science dissertation topics, then choose from this field. It will allow you to demonstrate a paper with information that can improve your learning and assimilation power altogether. So if you are into software and programming languages and want to make coding your forte, then you should pick from the 20 best Computer Science dissertation ideas:

  • Web-based document management system created using Microsoft SQL Server, J2EE, and XML markup languages
  • Creating a system for mapping work and scheduling rooms using software frameworks like the Microsoft.NET Framework
  • Application and assessment of the best algorithm for calculating association rules in a particular environment
  • Implementation and assessment of the best cluster-generation algorithm
  • Implementation and assessment of the best algorithm for producing the best and nearly best classification trees
  • Heuristic algorithm implementation and assessment for computing association rules
  • Custer-generating heuristic algorithm implementation and evaluation
  • Heuristic algorithm implementation and assessment for producing ideal and nearly ideal classification trees
  • Various methods for creating intelligent database interfaces, which offer a paradigm for programming databases without being familiar with SQL and tables
  • Fault-Tolerant Interconnection Network Routing using Multiple Passes and Constant Control Variables
  • Analysis of sorting networks' fault-tolerance
  • Framework for analysing, designing, and implementing web service security
  • Hardware and residue number system-based high-speed computing
  • The use of quick algorithms for one-way hashing functions and their evaluation
  • Various methodologies for testing embedded software systems
  • A dynamic proxy-based architecture design process for distributed Java objects in a mobile environment
  • The serialisation of modular data and mobile code
  • There are several ways to enhance open web architectures
  • Aflexible online learning environment
  • Design and implementation of a device-independent passenger information system for tracking vehicles (buses, cars, and taxis)

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IT themes are the most popular Computer Science dissertation ideas because they will work generically. Also, it is the fastest-growing sector regarding technology and digital platform optimisation. So, if you want to write a dissertation that can serve you with all the possible learning elements of IT, then choose from the topics given below:

  • Information system construction challenges for large healthcare organisations like the NHS UK
  • Standards for electronic hiring: Issues and Future Directions
  • The opportunities and challenges of switching to web-based information services
  • Web Environment Change Management
  • The nature of the required web space is evolving
  • An examination of cooperative social network tools for the collection and categorisation of data from young, middle-aged, and elderly people
  • Government initiatives in the UK for ICT adoption and diffusion, including e-government services and high-speed Internet access for consumers and citizens
  • Effects of publishing on libraries' future
  • Web's effect on library patrons
  • Putting in place a new, integrated information system for the library
  • Full-text databases' effects on search engine functions
  • Effects of full-text databases on people who use shopping carts
  • The Internet and cyber infrastructure's effects on UK employment and income
  • The Internet and cyber infrastructure's effects on marketing and marketing users in the UK
  • Implications for information retrieval and information-seeking behaviour
  • Students' use of the information age and scientific innovation in the classroom
  • Graduating students (undergraduate and graduate) use scientific innovation and information society
  • Measuring the effects of applications on language use and incorporating multimedia and the web into language planning
  • The impact of internet-based services, goods, and technologies on e-marketing, customer service, and usage
  • Various electronic marketing service models utilise computers, networks, and the Internet

Suppose you are still trying to decide on your theme selection, Forensic Computer Science dissertation examples might be a little tricky for your paper. But if you dare to choose this field, you will impress your professor. Which is a vital core responsibility you have? Having some extra marks will never hurt. So to do something unusually better, pick an unusual topic. Then it would help if you had dissertation writers assistance.

  • The computer has facilitated the transfer of information between businesses
  • Businesses and online consumers are becoming more integrated thanks to computer scientists
  • Online voting is now simple and easy, thanks to the creation of new computer software
  • How online libraries have facilitated book access for underprivileged students?
  • Utilising computer software to assist underserved communities in accessing medical care
  • Through the study of computer science, Africa is changing
  • A day in a computer scientist's shoes
  • Why is working in computing so difficult and time-consuming?
  • How have computers taken the place of letters and other forms of communication?
  • Using computer science to solve issues affecting online businesses
  • How studying computer science is simple for math lovers?
  • The function of computers in the operation of machines and medical equipment
  • The role of computer developers in regulating the global trade in goods
  • How are computer scientists using new software to address contemporary problems?
  • Addressing the issues with online learning that the world's rapid change has created
  • How do communities support the development of computer scientists?
  • Dissemination of essential computer science knowledge worldwide
  • Typical errors made by students learning about computing
  • Why having a solid mathematical foundation is helpful when studying computers?
  • How forensics is aided by computer science

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According to experts with Computer Science dissertation ideas, these are the various computer themes students can use to play and learn. They will be finished quickly and easily. If you enjoy them and have more time, you can go over these topics in greater detail and learn more about computers.

You will likely have a tonne of work on your hands, and you must find a way to avoid being stuck with the dissertation topic. Learning new things is enjoyable, and if you are devoted;, learning further information about various computer concepts might be your most enjoyable activity. However, you can only take advantage of this time if you are not working on academic assignments, exams, projects, tests, revisions, or other obligations.

Assignmentdesk.co.uk can relieve you of some of them by providing you with suggestions for your Computer Science dissertation ideas. And getting help from us will be the best option because we are skilled at producing dissertations for HD-worthy students.

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221 Interesting Thesis Topics for IT Students

it thesis topics

Did you know that one of the most important parts of writing your dissertation is finding the best topic possible? You are probably having serious problems finding a topic for your thesis. After all, the thesis topics IT students are looking for are pretty rare. The reality is that in the IT field, most topics have already been written about. There are few things left to write it seems. Well, things are a bit different. We are here to assure you that you can find thesis topics for IT students. Also, we want to assure you that it is not at all difficult to find an interesting topic that you can write an engaging paper about. We will provide you with 21 such topics shortly. College students can use our topics for free; we are very happy to help!

Writing Your Thesis and Looking for Dissertation Topics?

  • Why Thesis Topics for IT Students Are Important?
  • Fresh Dissertation Topics for You

Best IT Thesis Topics in Artificial intelligence

Exceptional it thesis topics in computer science and engineering, refreshing it thesis topics in communication and media, top it thesis topics on food technology, thoughtful it thesis topics on technology and human identity, top it thesis topics on pharmaceutical technologies, it thesis topic ideas on energy power technologies, it thesis topics on medical devices and diagnostics, it thesis topics on biotechnology, more interesting it thesis topics for you, need more it dissertation topics.

As you are probably already aware, the IT field is advancing rapidly. Advancements are made almost daily in technology, including information technology. This is why so many students are looking for fresh 2022 dissertation topics. They want to write about the latest technologies and the latest gadgets. Of course, one can go online and find various 2022 thesis topics IT students would find impressive. You will probably find some that are relatively decent. But be aware that the evaluation committee will most certainly not be impressed by decent topics. They want something new. They want something that can pique their interest. They want to LEARN something from you. And they want to award you with some bonus points. Why not take them?

Why Thesis Topics for IT Students Are Important

Did you ever wonder why so many people dedicate so much time to finding a great topic? Probably not. Let’s shed some light on this. College students are looking for IT dissertation topics because they want bonus points. The topic is the first thing the evaluation committee sees. It is the most important part of your paper. As such, it must be interesting, engaging, and also helpful. It must show that you have put in the effort to write the dissertation. Awe the admission committee and you will surely get bonus points. Even if your dissertation is not the best, you will still get a good score if the topic you choose is exceptional. But engaging IT dissertation topics are difficult to come by. Most of your classmates have already picked the simple ones. But you are not like the rest of your class, are you? You want to be original and you want to make a lasting impression on the professors. This is why you need to take a look at our fresh dissertation topics.

21 Fresh Dissertation Topics for You (Absolutely Free)

Without further ado, here are the 21 thesis topics for IT students that we think are the most interesting and engaging:

  • Conducting virtual business in the era of 3D Internet – the business of the future
  • Analyzing e-tourism services in the UK: Factors that Influence Customer Satisfaction
  • Mobile government applications and their benefits
  • Producing believable emotions using AI systems for e-commerce
  • The future of YouTube and multimedia distribution platforms
  • Analyzing the impact of media technology on child development throughout the school
  • Integrating an ERP system with a cloud service
  • Developing a tool to analyze keystrokes and use the data for password security
  • Analyzing critical vulnerabilities of the Android mobile operating system
  • Analyzing the impact of e-publishing on libraries (one of the best thesis topics for IT students)
  • In-depth analysis of the fault-recovery and redundancy in modern 4G mobile networks
  • The impact of full-text databases on Google as a search engine
  • Creating software capable of reading human emotions using a webcam
  • How effective is face recognition as a security measure?
  • Analyzing critical security vulnerabilities in IT systems used at the government level
  • Does curbing software piracy in developing countries have any negative results?
  • Using BitTorrent systems for faster multimedia delivery and playback
  • How safe are whistleblowers operating on the Dark Web? (one of the thesis topics IT students are usually reluctant to write about)
  • Building a Dark Web crawler that indexes onion sites based on specific criteria
  • Creating a modern Tetris game in C# using OpenGL
  • The advantages brought by mobile working to IBM and its employees

If you want to write a relevant research topic, consider writing about Artificial intelligence topics (AI). AI is a relevant phenomenon, and here is a look at some ideas of artificial intelligence that you should look into.

  • Is deep learning an effective way of dealing with deep learning?
  • How do artificial neural networks affect deep learning?
  • Discuss the areas of life machine learning that are most influential.
  • Ways to select the best algorithm for machine learning.
  • How does NASA use robotics?
  • Discuss the process of using natural languages to create a unique language.
  • How does artificial intelligence affect computer vision?
  • Compare and contrast the effects of supervised vs. unsupervised machine learning.
  • The effects of reinforcement machine learning algorithms.
  • Model-based vs. Model-free reinforcement learning algorithms.
  • Deep learning as a subject of machine learning.
  • Comparison between single vs. Multi-agent reinforcement learning.
  • Ways that the social robots interact with the humans
  • How do chatbots aid in the natural language processing system?
  • Five ways of computer vision application.
  • What is the recommended systems approach?
  • What is the interconnection of the Internet of things and artificial intelligence?
  • What amount of data is generated by the Internet of things devices?
  • Compare and contrast content-based recommendation vs. collaborative filtering.
  • What makes the collaborative filtering system stand out?

Computer science and engineering combine two different yet interconnected worlds of machines. The use of computer science uses the computer’s brain. It is, in most cases, used to include areas of studies like programming language and algorithms. Here is a list of research topics in computer science and engineering that you can use.

  • In what ways is the virtual and human perception connected?
  • What is the future of computer science-assisted education?
  • What are computer science and high-dimensional data modeling?
  • The imperative vs. declarative languages.
  • Explain the use of blockchain and AI algorithmic regulations.
  • How has blockchain technology impacted the banking industry?
  • In what way does machine architecture use to affect the efficiency of code?
  • What are the languages of parallel computing?
  • Explain the way that mesh generation is used for computational domains.
  • The cyber-physical optimization vs. the sensor networks.
  • Explain the development of computer graphics in a photorealistic rendering case.
  • What are game theory and network economics?
  • What are the most effective cryptographic protocols?
  • An overview of the software security types.
  • It is possible to eliminate phishing.
  • Floating point and programming language
  • In what ways is the mesh generation used for computational domains?
  • How to get the persistent data structure optimization
  • In what ways does computer thinking affect science?

One of the first areas that technology affected was communication. With technology, media is used for social interactions, business development, and educational purposes. Here are exciting ideas to use when researching your IT thesis paper.

  • What is the impact of ethics on communication?
  • How the development of communication through the computer has evolved in the past decade.
  • In what ways has social media impacted communication?
  • What role do media play during a disaster? Does it increase panic or help in reducing it?
  • Compare and construct the authority’s media presence in different countries.
  • Will people start preferring newspapers to new media again?
  • In what ways has the Internet changed media?
  • Discuss communication networks.
  • What impact do social media have on super bowl ads?
  • What are the new content marketing ideas?
  • What is the impact of media exposure on adolescents?
  • In what ways do people use hype in the media?
  • Discuss the media and freedom of speech.
  • Is it possible for people to build trustful relationships in virtual communication?
  • What measures can you put to maintain privacy on social media?
  • In what ways have computers changed interpersonal communications?
  • What is yellow journalism in new media?
  • In what ways do enterprises use ICT to get a competitive advantage?
  • Is it possible to live without mass media?
  • What are the impacts of mass media and morality in the 21st century?

If you are searching for a qualitative research topic about technology in the food industry, here is a list of ideas you can use.

  • What are the machines used in the food industry?
  • In what ways do robots improve safety in butcheries?
  • 3D printing and the food industry.
  • Is 3D printing the best solution to offer people with swallowing disorders?
  • About drones and precision agriculture.
  • In what ways does robotics help in creating eco-friendly food packages?
  • Is micro packaging the future?
  • Research on the development of edible cling film.
  • The solution that technology has to food waste.
  • How do preservatives and additives impact the human gut microbiome?
  • Physicochemical levels the effect of citric acid on orange juice.
  • Compare and contrast vegetable oil in mass production.
  • Time-temperature indicators and food industry.
  • Farming: hydroponic vs. conventional farming.
  • How is food safety a policy issue in agriculture today?
  • Ways you can use to limit the detection of parasites in food.
  • How is the baking industry evolving?
  • How technology is used to eliminate byproducts in edible oils production
  • About cold plasma and biofilm.
  • Ways to extract good antioxidant peptides are extracted from plants.

The ethical issues surrounding the enhancement technology are intertwined with the questions of human identity and the proper trajectory of human life. Here is a list of thesis ideas you can use in your research.

  • Does technology make human life worth living than animal life?
  • The dignity of human life concerning technology explained?
  • In what ways should humans be observed in informational technology?
  • Should tech and scientific investigations on humans have a limit?
  • What is the importance of DNA information in forming our identity?
  • Is Ancestry DNA testing important?
  • Explain multi-racial identification.
  • Can scientific investigations tell us what self-care is?
  • In what ways will virtual reality technology change us?
  • Should there be a limit on the research in virtual reality? The possibility of virtual reality being the future.
  • What are the benefits of using virtual reality technologies?
  • What is the importance of finding alternative treatments for mental illness other than drugs?
  • Has the increase in technology affected the rise of mental illness?
  • Ways technology can be used to control addiction.
  • Pros and cons of using technology to control brains.
  • 7 social dangers of the brain controlling technology.
  • Does science dictate who we are?
  • What has led to the increase in mental illness among tech enthusiasts?
  • Can tech-related mental illness be cured?
  • What is the relationship between technology and drug addiction?

Companies are using technology to search for ways they can use it to reduce costs and boost effectiveness by doing pharmaceutical technology research. Impress your lecturer by choosing one of the research topics discussed below

  • What is the effectiveness of medical therapy management?
  • Explain how prior electronic authorization is a pharmacy technology trend.
  • Explain the medical therapy management and the health information exchanges.
  • How can electronic prescribing reduce the possibility of drug abuse issues?
  • Ways that pharmacists help with meaningful tech use.
  • Discuss various pharmaceutical technologies.
  • Pharmaceutical technology research.
  • What are specialty medications?
  • Vaccines for AIDS: can it be developed?
  • Ways that the prescription drug monitoring program works.
  • How do specialty pharmacies use NCPDP?
  • Why are patients interested in real-time pharmacy?
  • Phenotypic screening research.
  • Impact of ERP with pharmaceutical company’s analytics.
  • Pharmaceutical technologies: data security.
  • About DNA-encoded library technology.
  • Pro and cons antibiotics vs. superbugs.
  • How does the body-on-a-chip approach be used for personalized medicines?
  • Modern cannabidiol medicine and pain management.
  • What is the future of cannabidiol medicine?

It is not possible to have a technology process without energy. That is the reason that scientists are always looking for ways they can improve energy power technologies. So, if you are looking for thesis topics you can use to impress your lecturer, here is a list of power technology research you can use.

  • Ways that fuel cells can be used for the generation of stationary power.
  • Compare the energy density of lithium-ions and lithium-air batteries.
  • Gasoline vs. Lithium-air batteries.
  • The pros and cons of renewable energy use.
  • How does the UAE use nuclear power?
  • Research on India power installation.
  • Increase in gas prices and alternative energy sources.
  • How can hydrogen energy be used to transform the methods or energy?
  • Is hydrogen energy the future?
  • About the thermal storage and AC systems.
  • In what ways can you use load balance using a smart grid?
  • How can distributed energy generation optimize power waster?
  • Is the smart energy network a solution to climate change?
  • What is the future of tidal power?
  • What is the possibility of 3D printing micro stirring engines?
  • In what ways can robots be used to adjust the solar panel weather?
  • Explain advanced biofuel and algae.
  • In what ways can photovoltaic glass be fully transparent?
  • Compare the different third-generation biofuels.
  • Is space-based solar power a myth or the reality of the future?

The innovation of medicine and technology helps to improve life expectancy. If you feel that saving lives is your purpose, here are some thesis topics you can use in your research paper.

  • The effects of robotic surgeries.
  • Explain defibrillator & cardiac resynchronization therapy.
  • How smart can inhalers be used as a new solution to asthma treatment?
  • Genetic counseling: ways of preventing diseases.
  • What are the benefits of electronic medical records?
  • How is Erythrocytapheresis used to treat sickle cell disease?
  • The reason that drug-eluting stents fail.
  • An overview of the dissolved brain sensors.
  • What are the benefits of 3D printing for medical purposes?
  • How soon will it be possible to create an artificial organ?
  • Research on wearable technologies in health care.
  • Precision medication based on genetics.
  • The importance of using virtual medicine devices for educational purposes.
  • Research on the development of telemedicine.
  • How is technology impacting cancer treatment?
  • Is genome editing safe?
  • How is the electronic diagnosis tool evolving?
  • Brain-machine interface, the future.
  • How does the use of wireless communication help medical professionals in hospitals?
  • Ten ways wearable technology impacts the medical industry.

The development of biotechnology allows people to cure diseases and help with new machines. Here are some ideas of interesting topics you can use for your biotechnology thesis research.

  • Ten impacts of biotechnology in farming.
  • How does biotechnology lead to a self-sufficient protein supply?
  • Evapotranspiration vs. Evaporation.
  • DNA cloning and a Southern blot.
  • How are personalized drugs made?
  • What is pharmacogenetics?
  • Is cloning playing God?
  • How is pharmacogenetics used to get cancer medicines?
  • Is it possible to control our genetics?
  • How much genetic control do humans have?
  • Based on genetics, at what point do we cease to be human?
  • Research on bioethics and stem cells.
  • Definition of genetic engineering.
  • Gene therapy and genetic engineering.
  • Ten benefits and risks of genetic engineering.
  • How does plant genetic enhancement help preserve scarce plants?
  • South Africa Y-chromosome genotyping.
  • Ways technology is used in the creation of new vaccines.
  • How does Nanotechnology help in treating HIV?
  • An overview of Genes in heavy metal tolerance.

Your IT thesis does not have to be boring. Here is a list of interesting thesis topics that will impress your lecturer.

  • Ways that you can eliminate heat-resistant microorganisms with ultraviolet light.
  • In what ways can pesticides be used to diagnose cancer?
  • How can the smeller nuclear reactors be more efficient?
  • An overview of renewable energy technologies.
  • Explain electronic use in the food industry and agriculture.
  • The harm of polyphenols in food.
  • Hope for anticancer nanomedicine.
  • Does increasing military technology make use safe?
  • What is the importance of military research?
  • In what ways can technology be used to gauge intelligence?
  • In what ways is Google search changing us?
  • Blogs vs. books.
  • How is teaching IT research skills important today?
  • Should parents and schools encourage or discourage social media?
  • Does Google affect the attention span of young people? What is the borderline in hardware and software cloud computing?
  • What will be the impact when everything moves to the cloud?
  • How will virtual reality change education?
  • If the computer takes over most of our tasks, what will humans do?
  • What will computer language be important in the future?
  • What are the benefits of robots in health care?

Of course, there are dozens of other thesis topics on which students could write a paper. Some companies specialize in providing college students with entire lists of topics on a specific subject. You just need to contact an online academic writing company and tell its writers what you need. These people have extensive experience in the IT industry and have probably written dozens of dissertations. They can help you with more dissertation topics. And the best part is that some of these online services are quite affordable. An exceptional topic is worth the money – guaranteed!

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dissertation topics for software systems

IT Dissertation Topics (26 Examples) For Your Academic Research

Mark Dec 28, 2019 Jun 5, 2020 Information Technology No Comments

We aim to offer a vast collection of IT dissertation topics. You can find a suitable topic from the list of IT dissertation topics presented below. Writing a dissertation on information technology topics has its challenges. However, the evolution in the field of information technology offers a wide scope of research. You can start with […]

IT dissertation topics

We aim to offer a vast collection of IT dissertation topics. Writing a dissertation on information technology topics has its challenges. However, the evolution in the field of information technology offers a wide scope of research. You can find suitable ideas from the list of IT research topics for your project as presented below.

Our team of expert writers can provide quality dissertations on the selected topics. We ensure that our work meets the required standards and deadlines.

A list Of IT dissertaton topics

Studying the technology-enhanced development of autonomous learning in tracking the student’s performance.

Role of e-HR systems in managing employee engagement and satisfaction.

Analysing the history and evolution of touch screen technology.

Exploring the concept of text mining and its pros and cons.

The extent to which social media has influenced the lives of humans in the 21st century.

How information systems are increasing the competencies of SMEs around the world?

How is education supporting the incorporation and development of new technologies?

To study the role of technology in controlling addictions.

The evolution of restaurant management systems and how it is helping restaurants in managing their day-to-day tasks?

Studying the importance of data mining and customer relationship management.

Examining the concept of e-commerce and the network security concerns in the context of SMEs.

Exploring the concept of the vehicle registration system and how it is helping in controlling traffic accidents and thefts.

Studying the threats of phishing email attacks on the online banking systems.

Exploring the opportunities of broadband technologies.

To study the creativity and effective electronic brainstorming concepts.

To find out the suitable methods of requirements modelling for business applications.

Investigating the piracy issues on the internet and how it affects the businesses.

Studying the systems dynamics approach in modelling the internet penetration.

The role of customer query tracker in the B2B models.

To study the best practices of a call intensive support desk and network operations centre.

Studying the impact of the information age on the modern-day society.

Analysing the server-based content adaptation architecture and its benefits.

A literature review on the development of interactive software engineering tools.

Conducting an investigation of cyber-crime based on internet piracy.

Examining the pros and cons of e-commerce solutions related to fashion businesses.

To analyse the impact of poor corporate intranet sites and their effects on staff performance in large enterprises.

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dissertation topics for software systems

Introduction

Software Engineering is a branch that deals with the development and evolution of software products by employing certain methodologies and well-defined scientific principles. For developing a software product certain processes need to be followed and outcome of which is an efficient and authentic software product. The software is a group of executable program code with associated libraries. Software designed to satisfy a specific need is known as Software Product. It is a very good topic for master’s thesis, project, and research. There are various topics in Software Engineering which will be helpful for M.Tech and other masters students write their software project thesis.

Latest thesis topics in software engineering for research scholars:

  • Fault detection in software using biological techniques
  • Enhancement in MOOD metrics for software maintainability and reliability
  • To enhance effort estimation using Function point analysis in Cocomo model
  • To evaluate and improve model based mutation technique to detect test cases error in product line testing
  • To propose improvement in genetic algorithm to calculate function dependency in test case prioritization in regression testing
  • To propose dynamic technique with static metrics to check coupling between software modules
  • To propose improvement TYPE 4 clone detection in clone testing

Find the link at the end to download the latest thesis and research topics in software engineering

Software Evolution

Software Evolution is the process of developing software product using underlying techniques and methodologies. It consists of all the steps right from the initial requirements up to its maintenance. In the initial stage, software requirements are gathered. After this, a prototype of the actual software product is created which is shown to the end users for feedback. Users give their suggestions regarding the product and suggest changes if required. This process is repeated until the time desired software product is developed.  There are certain Software Evolution laws according to which software is divided into following three types:

  • S-Type (static-type) – This type of software works according to specifications and solutions. It is the simplest of all the three types of software.
  • P-Type (practical-type) – This software is a collection of procedures. Gaming software is an example of this type of software.
  • E-Type (embedded-type) – This software works according to the real-world requirements. It has a high degree of evolution.

The methods and steps taken to design a software product are referred to as software paradigms .

Why is Software Engineering required?

Software Engineering is required due to frequent changes in user requirements and the environment. Through your thesis and research work, you can get to know more about the importance of Software Engineering. Following are the other things for which software engineering is required:

  • Large Software – The large size of software make it essential for the requirement of software engineering.
  • Scalability – Software Engineering makes it possible to scale the existing software rather than creating a new software.
  • Cost – Software Engineering also cut down the excess manufacturing cost in software development.
  • Dynamic Nature of Software – Software Engineering plays an important role if new enhancements are to be done in the existing software provided that the nature of software is dynamic.
  • Better Quality Management – Software Engineering provides better software development processes for better quality services.

Software Development Lifecycle (SDLC)

SDLC is a sequence of steps and stages in Software Engineering for the development of Software product. It is an important topic for project and thesis in software engineering. Following are the phases of SDLC:

Thesis in software engineering

  • Requirement Gathering and Analysis – It is the initial stage of software development in which the requirements for the software product to be made is collected. In this phase, the engineering team studies existing systems, take the opinion of stakeholders, and conduct user interviews. The types of requirements include user requirements, functional requirements and non-functional requirements. After the requirements are collected, these are examined and analyzed for validation i.e. whether these requirements can be incorporated into the system or not.
  • Feasibility Study – After requirement gathering, the next step is the feasibility study i.e. to check whether the desired software system can be made or not. The software development team comes up with an outline of the whole process and discusses whether the system will be able to meet the user requirements or not. In this phase, all the aspects like financial, practical, and technical are considered. If these aspects are found to be feasible only then the further processes are taken up.
  • Software Design – After confirming the feasibility of the software system, the designing of the software product is done. The designing of the software is done based on the requirements collected in the initial stage. An outline of the whole process is created in this phase which will define the overall system architecture. There are two types of designs – physical design and logical design.
  • Coding – This phase is also known as implementation phase as the actual implementation of the software system takes place here. An executable programming code is written in any suitable programming language for implementation. The work is divided into different modules and coding is done in each of these modules. This process is undertaken by a developer expert in programming.
  • Testing – Testing phase follows the coding phase in which testing of the code is done to check whether the system meets the user requirements or not. The types of testing include unit testing, system testing, integration testing and acceptance testing. Testing is required to find out any underlying errors and bugs in the product. Testing helps in creating a reliable software product.
  • Deployment – After successful testing, the software product is delivered to the end users. Customers perform Beta Testing to find out if there are changes required in the system or not. If changes are needed, then they can suggest them to the engineering team.
  • Maintenance – A special team is appointed to look after the maintenance of the software product. This team will provide timely software updates and give notifications based on that. The code is updated in accordance with the changes taking place in the real world environment.

Software Development Process Models

There are certain software development models as defined by Software Paradigms. Some of these are explained below:

Waterfall Model

It is a simple model for software development which defines that all the phases of SDLC take place in a linear manner. Simple meaning that if one phase is finished then only the next phase is started. According to this model, all the phases are executed in sequence with the planning of next phase in the previous phase. Also, this model will not function properly if there are certain issues left in the previous phase.

dissertation topics for software systems

Iterative Model

It is another model for software development in which the whole process takes place in iterations. Iteration simply means repeating steps after a cycle is over. On the first iteration, the software is developed on a small scale and then the subsequent steps are followed.  During the next iteration, more features and modules are added. On completion of each iteration cycle, software is produced which have their own features and capabilities. The management team works on the risk management and prepare for next iteration.

dissertation topics for software systems

Spiral Model

Spiral Model is a combination of iterative model and any one of the other SDLC model. The most important feature of this model is the consideration of risk factor which left unnoticed by other models. Initially, the objectives and constraints of the software product are determined. During next iteration, the prototype of the software is created. This process also includes risk analysis. In the fourth phase, next iteration is prepared.

dissertation topics for software systems

In the waterfall model, we can go to next step only if the previous step is completed. Also, we cannot go back to the previous stage if some change is required. This drawback of waterfall model is fulfilled by the V-Shaped Model which provides testing of each phase in a reverse manner. In this model, test plans and test cases are created according to the requirements of that stage to verify and validate the software product. Thus verification and validation go in parallel in this case.

dissertation topics for software systems

Software Metrics and Measures

Software Metrics and Measures are essential components in Software Engineering to understand the attributes and aspects of a software. These also help in maintaining the better quality of the software products. Following are some of the Software Metrics:

  • Size Metrics – It is measured in terms of Lines of Code (LOC) and Function Point Code. Lines of Code mean the number of lines of the programming code whereas Function Point Code is the Functional capacity of the software.
  • Complexity Metrics – It is measured in terms of number of independent paths in a program.
  • Quality Metrics – It is determined by the number of defects encountered while developing the software and after the product is delivered.
  • Process Metrics – Methods, tools, and standards used in software development come under process metrics.
  • Resource Metrics – It includes effort, time and resources used in development process.

Modularization in Software Engineering

Modularization is a technique in Software Engineering in which software system is divided into multiple modules and each module carries out its individual task independently. Modularization is more or less based on ‘Divide and Conquer’ approach. Each module is compiled and executed separately.

Advantages of Modularization are:

  • Smaller modules are easier to process.
  • Modularization offers a level of abstraction to the program.
  • High Cohesion components can be used again.
  • Concurrent execution is also possible.
  • It is also more secure.

Software Testing

It is the process of verifying and validating the software product to check whether it meets the user requirements or not as expected. Moreover, it also detects underlying defects, errors, and bugs that left unnoticed during the process of software development. As a whole, software testing detects software failures. Software Testing itself is a sub-field in software engineering and a trending topic for project, thesis, and research in software engineering.

Purpose of Software Testing

Following are the main purposes of software testing:

  • Verification – Verification is a process to find out whether the developed software product meets the business requirements or not. Verification ensures that whether the product being created satisfies the design specifications or not.
  • Validation – Validation is the process that examines whether or not the system meets the user requirements. The validation process is carried out at the end of SDLC.
  • Defect Finding – Defect finding simply means the difference between the actual output and the expected output. Software Testing tends to find this defect in the software product.

Types of Testing

Following are the main types of testing in software systems:

  • Alpha Testing – It is the most common type of testing carried out by a developer team at the developer end. It is conducted before the product is released.
  • Beta Testing – It is a type of software testing carried out by end users at the user end. This type of testing is performed in a real-world environment.
  • Acceptance Testing – It is a type of testing to find out whether the software system meets the user requirements or not.
  • Unit Testing – It is a type of testing in which an individual unit of the software product is tested.
  • Integration Testing – In this, two or more modules are combined and tested together as a group.
  • System Testing – Here all the individual modules are combined and then tested as a single group.

UML and Software Engineering

UML or Unified Modeling Language is language in software engineering for visualizing and documenting the components of a software system and is created by Object Management Group (OMG). It is different from programming languages. UML implements object-oriented concepts for analysis and design.

Building Blocks of UML

Following are the three main building blocks of UML:

Relationships

Things can be any one of the following:

Structural – Static Components of a system

Behavioral – Dynamic Components of a system

Grouping – Group elements of a UML model like package

Annotational – Comments of a UML model

The relationship describes how individual elements are associated with each other in a system. Following kinds of relationships are there:

  • Association
  • Generalization
  • Realization

The output of the entire process is UML diagrams. Following are the main UML diagrams:

  • Class Diagram
  • Object Diagram
  • Use Case Diagram
  • Sequence Diagram
  • Collaboration Diagram
  • Activity Diagram
  • Statechart Diagram
  • Deployment Diagram
  • Component Diagram

Software Maintenance

After the Software product is successfully launched in the market, timely updations and modifications needed to be done. This all comes under Software Maintenance. It includes all those measures taken after the delivery to correct errors and to enhance the performance. Software Maintenance does not merely means fixing defects but also providing time to time updations.

Types of Software Maintenance

The types of Software Maintenance depends upon the size and nature of the software product. Following are the main types of software maintenance:

  • Corrective Maintenance –  Fixing and correcting a problem identified by the user comes under corrective maintenance.
  • Adaptive Maintenance –  In adaptive maintenance, the software is kept up-to-date to meet the ever-changing environment and technology.
  • Perfective Maintenance –  To keep the software durable, perfective maintenance is done. This includes the addition of new features and new user requirements.
  • Preventive Maintenance –  To prevent any future problems in the software, preventive maintenance is done so that there are not any serious issues in near future.

Activities in Software Maintenance

Following activities are performed in Software Maintenance as given by IEEE:

  • Identification and Tracing
  • Implementation
  • System Testing
  • Acceptance Testing
  • Maintenance Management

Reverse Engineering

Reverse Engineering is a process in which an existing system is thoroughly analyzed to extract some information from that system and reproduce that system or product using that extracted information.  The whole process is a reverse SDLC. Reverse Engineering for software is done to extract the source code of the program which can be implemented in a new software product.

Case Tools for Software Engineering

Case or Computer-aided Software Engineering are computer-based automated tools for development and maintenance of software products. Just as the CAD (Computer-aided design) is used for designing of hardware products, Case is used for designing of software products. Case tools develop high-quality and easily maintainable software products.

Elements of Case Tools

Following are the main components of Case Tools:

  • Central Repository –  Central Repository or Data Dictionary is a central storage for product specifications, documents, reports, and diagrams.
  • Upper Case Tools – These are used in planning, analysis, and design phases of SDLC.
  • Lower Case Tools – These are used in the implementation, testing, and maintenance.
  • Integrated Case Tools – These tools can be used in all the stages of SDLC.

Project, Thesis, and Research topics in Software Engineering

Following is the list of Software Engineering topics for project, thesis, and research for masters and other postgraduate students:

  • Data Modeling

Software Models

Software Quality

Verification and Validation

Software Project Management

Data Modeling 

The process of structuring and organizing data is known as Data Modeling. After structuring of data, it is implemented in the database system. While organizing data, certain constraints and limitations are also applied to data. The main function of Data Modeling is to manage a large amount of both structured and unstructured data. In data modeling, initially, a conceptual data model is created which is later translated to the physical data model.

UML(Unified Modeling Language)

This was all about Software Engineering. You can explore and research more of this topic while working on your project and thesis. It is a standard language to visualize software systems. This language is used by software developers, business analysts, software architects, and other individuals to study the artifacts of a software system. It is a very good topic for a thesis in Software Engineering.

SDLC or Software Development Lifecycle is a set of stages followed for the development of a software product. For building a software product steps are followed beginning from data collection to software maintenance. It also includes software testing in which a software goes through various types of testing before giving a final nod to the software product.

Masters students can work on software models for their thesis work. Various types of software models are there like waterfall model, V-Shaped model, spiral model, prototype model, agile model, Iterative model etc. These models give step by step implementation of various phases of software development.

The concept of ontology is used in Software Engineering to represent the domain knowledge in a formal way. Certain knowledge-based applications use the ontology to share knowledge. Ontology is used in software engineering to collaborate the use of AI techniques in software engineering. UML diagrams are also being used in the development of Ontology.

Software Quality refers to the study of software features both external and internal taking into consideration certain attributes. External features mean how software is performing in a real-world environment while internal features refer to the quality of code written for the software. External quality is dependent on the internal in the sense that software works in the real-world environment with respect to the code written by the coder.

After the software product is implemented, it goes through the testing phase to find any underlying error or bug. The most common type of software testing is the alpha testing. In this type of testing, the software is tested to detect any issue before it is released. Students can find a number of topics under software testing for thesis, research, and project.

Software Maintenance is necessary as some errors or bugs can be detected in future in the software product. Students can study and research on the types of software maintenance done by the team. Software Maintenace does not solely means fixing errors in the software. It includes a number of tasks done so that the software product keeps on working perfectly with advancements.

Verification and Validation are the two most important steps in software engineering. Verification and Validation are not as easy as it seems. There are a number of steps under it which can be an interesting research work for your thesis. Verification is done before validation.

It is another interesting topic for the thesis in software engineering. It refers to the management of the software project through proper planning and execution. It includes time, cost, quality, and scope of the project. A team is appointed for this purpose.

These were the topics in software engineering for project, thesis, and research. Contact us for any kind of thesis help in software engineering for M.Tech and Ph.D.

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  • Bibliography
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Dissertations / Theses on the topic 'SDN - Software-Defined Networking'

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Pitzus, Antonio. "SDN : Software Defined Networking." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14006/.

Tseng, Yuchia. "Securing network applications in software defined networking." Thesis, Sorbonne Paris Cité, 2018. http://www.theses.fr/2018USPCB036.

Hossain, Md Billal. "QoS-Aware Intelligent Routing For Software Defined Networking." University of Akron / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=akron1595086618729923.

Aydeger, Abdullah. "Software Defined Networking for Smart Grid Communications." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2580.

Jiménez, Agudelo Yury Andrea. "Scalability and robustness in software-defined networking (SDN)." Doctoral thesis, Universitat Politècnica de Catalunya, 2016. http://hdl.handle.net/10803/397652.

Adduci, Pietro. "Software-Defined Networking: lo standard Openflow." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/7241/.

Cerboni, Simone Marco. "Software Defined Networking for The Internet of Things." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016.

Nyberg, Tihmmy. "Introduktion till Software Defined Networking : Utvärdering av kontroller." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-39380.

Kim, Hyojoon. "Facilitating dynamic network control with software-defined networking." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53939.

Ahmad, I. (Ijaz). "Improving software defined cognitive and secure networking." Doctoral thesis, Oulun yliopisto, 2018. http://urn.fi/urn:isbn:9789526219516.

Pagola, Moledo Santiago. "Vendor-Independent Software-Defined Networking : Beyond The Hype." Thesis, Linköpings universitet, Databas och informationsteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157456.

Fahlén, Tony. "En jämförande studie mellan Software-Defined Networking protokollen OpenFlow & OpFlex." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-35565.

Forgione, Alessandro. "Openflow e software-defined networking: l'evoluzione della rete programmabile." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/7919/.

Tanyingyong, Voravit. "Performance and Reliability in Open Router Platforms for Software-Defined Networking." Licentiate thesis, KTH, Network Systems Laboratory (NS Lab), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-144285.

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Liver, Toma, and Mohammed Darian. "Soft Migration from Traditional to Software Defined Networks." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-44265.

Rotsos, Charalampos. "Improving network extensibility and scalability through SDN." Thesis, University of Cambridge, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.709033.

Bispo, Pedro José Neves. "A software defined network controller quantitative and qualitative analysis." Master's thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/23475.

Ridolfi, Pietro. "SDN: il futuro della rete - stato dell'arte e casi reali." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/9107/.

Carpa, Radu. "Energy Efficient Traffic Engineering in Software Defined Networks." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEN065/document.

Nasim, Kamraan. "AETOS: An Architecture for Offloading Core LTE Traffic Using Software Defined Networking Concepts." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35085.

Aklamanu, Fred Kwasi Mawufemor. "Intent-based networking for 5G mobile networks." Thesis, Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAS013.

Tammana, Praveen Aravind Babu. "Software-defined datacenter network debugging." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31326.

Kamaruddin, Amalina Farhan. "Experimentation on dynamic congestion control in Software Defined Networking (SDN) and Network Function Virtualisation (NFV)." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/16917.

Scalzotto, Luca. "Software Defined Networking-enabled IoT Middleware for Event Prioritization in Emergency Scenarios." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17390/.

Calabrigo, Adam Chase. "SD-MCAN: A Software-Defined Solution for IP Mobility in Campus Area Networks." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1797.

Sahay, Rishikesh. "Policy-driven autonomic cyberdefense using software-defined networking." Thesis, Evry, Institut national des télécommunications, 2017. http://www.theses.fr/2017TELE0022/document.

Berriri, Asma. "Model based testing techniques for software defined networks." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL017/document.

Olivi, Matteo. "Design of a Kubernetes-based Software-Defined Network Control Plane." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.

Rivera, Polanco Sergio A. "AUTOMATED NETWORK SECURITY WITH EXCEPTIONS USING SDN." UKnowledge, 2019. https://uknowledge.uky.edu/cs_etds/87.

Jamaliannasrabadi, Saba. "High Performance Computing as a Service in the Cloud Using Software-Defined Networking." Bowling Green State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1433963448.

Franková, Barbora. "Zákonné odposlechy v SDN." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234982.

Aimi, Leonardo. "Orchestrazione di Risorse Distribuite in Scenari Network Function Virtualization e Software Defined Networking Integrati." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

Niyaz, Quamar. "Design and Implementation of a Deep Learning based Intrusion Detection System in Software-Defined Networking Environment." University of Toledo / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1501785493311223.

Marciniak, Petr. "Vyvažování zátěže v sítích OpenFlow." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236205.

Isolani, Pedro Heleno. "Interactive monitoring, visualization, and configuration of openflow-based SDN." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2015. http://hdl.handle.net/10183/127452.

Ekanayake, Mudiyanselage Wijaya Dheeshakthi. "An SDN-based Framework for QoSaware Mobile Cloud Computing." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35117.

Arbiza, Lucas Mendes Ribeiro. "SDN no contexto de IoT : refatoração de middleware para monitoramento de pacientes crônicos baseada em software-defined networking." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/134368.

Alasadi, Emad Younis. "Enhancing network scalability by introducing mechanisms, architectures and protocols." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/15874.

Alharbi, Faisal. "SDN-BASED MECHANISMS FOR PROVISIONING QUALITY OF SERVICE TO SELECTED NETWORK FLOWS." UKnowledge, 2018. https://uknowledge.uky.edu/cs_etds/72.

Ceron, João Marcelo. "MARS: uma arquitetura para análise de malwares utilizando SDN." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-28022018-105426/.

Zacarias, Iulisloi. "Employing concepts of the SDN paradigm to support last-mile military tactical edge networks." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/183191.

Renzi, Gianluca. "Controllo generalizzato via software di dispositivi per l'interconnessione flessibile di data center." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8524/.

Hasan, Hasanein. "Enhancing performance of conventional computer networks employing selected SDN principles." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/14457.

Barattini, Daniel. "Supporto a micro-servizi per controller SDN ad alta scalabilità e affidabilità." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21428/.

Ijiga, Owoicho Emmanuel. "SDN-based adaptive data-enabled channel estimation in the internet of maritime things for QoS enhancement in nautical radio networks." Thesis, University of Pretoria, 2021. http://hdl.handle.net/2263/78709.

Gruesen, Michael G. "Towards an Ideal Execution Environment for Programmable Network Switches." University of Akron / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=akron1468834070.

Henriksson, Johannes, and Alexander Magnusson. "Impact of using cloud-based SDNcontrollers on the networkperformance." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-44152.

Hölscher, Anton. "The Latency Effects of Utilizing a Microservice Architecture in a Time-Critical System." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-178295.

van, 't Hof David M. "Service Provisioning in SDN using a Legacy Network Management System." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-204957.

Silva, Eduardo Germano da. "A one-class NIDS for SDN-based SCADA systems." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2007. http://hdl.handle.net/10183/164632.

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Heavy Machinery Meets AI

  • Vijay Govindarajan
  • Venkat Venkatraman

dissertation topics for software systems

Until recently most incumbent industrial companies didn’t use highly advanced software in their products. But now the sector’s leaders have begun applying generative AI and machine learning to all kinds of data—including text, 3D images, video, and sound—to create complex, innovative designs and solve customer problems with unprecedented speed.

Success involves much more than installing computers in products, however. It requires fusion strategies, which join what manufacturers do best—creating physical products—with what digital firms do best: mining giant data sets for critical insights. There are four kinds of fusion strategies: Fusion products, like smart glass, are designed from scratch to collect and leverage information on product use in real time. Fusion services, like Rolls-Royce’s service for increasing the fuel efficiency of aircraft, deliver immediate customized recommendations from AI. Fusion systems, like Honeywell’s for building management, integrate machines from multiple suppliers in ways that enhance them all. And fusion solutions, such as Deere’s for increasing yields for farmers, combine products, services, and systems with partner companies’ innovations in ways that greatly improve customers’ performance.

Combining digital and analog machines will upend industrial companies.

Idea in Brief

The problem.

Until recently most incumbent industrial companies didn’t use the most advanced software in their products. But competitors that can extract complex designs, insights, and trends using generative AI have emerged to challenge them.

The Solution

Industrial companies must develop strategies that fuse what they do best—creating physical products—with what digital companies do best: using data and AI to parse enormous, interconnected data sets and develop innovative insights.

The Changes Required

Companies will have to reimagine analog products and services as digitally enabled offerings, learn to create new value from data generated by the combination of physical and digital assets, and partner with other companies to create ecosystems with an unwavering focus on helping customers solve problems.

For more than 187 years, Deere & Company has simplified farmwork. From the advent of the first self-scouring plow, in 1837, to the launch of its first fully self-driving tractor, in 2022, the company has built advanced industrial technology. The See & Spray is an excellent contemporary example. The automated weed killer features a self-propelled, 120-foot carbon-fiber boom lined with 36 cameras capable of scanning 2,100 square feet per second. Powered by 10 onboard vision-processing units handling almost four gigabytes of data per second, the system uses AI and deep learning to distinguish crops from weeds. Once a weed is identified, a command is sent to spray and kill it. The machine moves through a field at 12 miles per hour without stopping. Manual labor would be more expensive, more time-consuming, and less reliable than the See & Spray. By fusing computer hardware and software with industrial machinery, it has helped farmers decrease their use of herbicide by more than two-thirds and exponentially increase productivity.

  • Vijay Govindarajan is the Coxe Distinguished Professor at Dartmouth College’s Tuck School of Business, an executive fellow at Harvard Business School, and faculty partner at the Silicon Valley incubator Mach 49. He is a New York Times and Wall Street Journal bestselling author. His latest book is Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future . His Harvard Business Review articles “ Engineering Reverse Innovations ” and “ Stop the Innovation Wars ” won McKinsey Awards for best article published in HBR. His HBR articles “ How GE Is Disrupting Itself ” and “ The CEO’s Role in Business Model Reinvention ” are HBR all-time top-50 bestsellers. Follow him on LinkedIn . vgovindarajan
  • Venkat Venkatraman is the David J. McGrath Professor at Boston University’s Questrom School of Business, where he is a member of both the information systems and strategy and innovation departments. His current research focuses on how companies develop winning digital strategies. His latest book is Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future.  Follow him on LinkedIn . NVenkatraman

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Revenue of artificial intelligence system software companies South Korea 2018-2022

In 2022, the sales revenue of artificial intelligence (AI) system software companies in South Korea was estimated to be around 540.9 billion South Korean won. This was a large increase from the previous year. The survey defines system software as framework tools required for AI operations, such as engines or Application Programming Interfaces (APIs).

Sales revenue of artificial intelligence (AI) system software companies in South Korea from 2018 to 2022 (in billion South Korean won)

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South Korea

2018 to 2022

1,624 companies in 2022

Face-to-face interview, online survey

*Estimate. Figures have been rounded. 1,000 South Korean won equals 0.75 U.S. dollars or 0.69 euros as of February 2024. Respondent counts for previous years are as follows: 2018: 612 companies 2019: 662 companies 2020: 1,199 companies 2021: 1,274 companies

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dissertation topics for software systems

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dissertation topics for software systems

Cyber-crime

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U-Haul tells 67K customers that cyber-crooks drove away with their personal info

Thieves broke into it system using stolen login.

U-Haul is alerting tens of thousands of folks that miscreants used stolen credentials to break into one of its systems and access customer records that contained some personal data.

A U-Haul spokesperson told The Register that about 67,000 customers in the United States and Canada were affected, but declined to answer other questions about the security snafu.

The intrusion happened on December 5, according to letters going out this week to those affected. After investigating the break-in with the help of an outside cybersecurity firm, the moving and truck rental giant determined crooks accessed its U-Haul Dealer and Team Members system used to track reservations and view customer records. 

These customers' records contained personal information, including names, dates of birth, and driver license numbers. No financial information was stolen, according to U-Haul.

dissertation topics for software systems

"The customer record system that was involved is not part of our payment system," the biz said in its notification letter [ PDF ]. "No payment card data was involved."

U-Haul says it hardened its security systems to help prevent future breaches. Specifically, this included changing passwords on compromised accounts and offering affected customers a free, one-year membership with Experian IdentityWorks Credit 3B.

  • Cyberattack downs pharmacies across America

Orgs are having a major identity crisis while crims reap the rewards

Alphv gang claims it's the attacker that broke into prudential financial, loandepot.

  • LockBit identity reveal a bigger letdown than Game of Thrones Season 8

While the U-Haul spokesperson declined to comment on how the criminals obtained the compromised credentials — eg, from an earlier data dump, or a social-engineering campaign — the incident illustrates how these types of identity-related attacks have skyrocketed over the past year.

IBM X-Force, in a threat intelligence report published earlier this week, reported a 71 percent year-over-year increase in the volume of attacks using valid credentials in 2023. 

In fact, compromised accounts represented 30 percent of all incidents that the IT giant's incident response team assisted with last year.

On a related note: X-Force also found that cloud account credentials make up 90 percent of for-sale cloud assets on the dark web.

Meanwhile, CrowdStrike's 2024 Global Threat Report , also published this week, found a similar increase in identity-related threats. In addition to using stolen credentials, the outfit's threat intel team spotted attackers targeting API keys and secrets, session cookies and tokens, one-time passwords, and Kerberos tickets.

"Threat actors have really focused on identity – taking a legitimate identity, logging in as a legitimate user, and then laying low, staying under the radar by living off the land and using legitimate tools," Adam Meyers, head of counter adversary operations at CrowdStrike, told The Register in an earlier interview . ®

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dissertation topics for software systems

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IMAGES

  1. List of Software Engineering Dissertation Topics and Titles

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  2. (PDF) Exploring Software Systems

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  24. Prompt engineering is a task best left to AI models

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  29. U-Haul says 67K customers' data was stolen in cyberattack

    U-Haul is alerting tens of thousands of folks that miscreants used stolen credentials to break into one of its systems and access customer records that contained some personal data. A U-Haul spokesperson told The Register that about 67,000 customers in the United States and Canada were affected, but declined to answer other questions about the ...