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 (moodle).

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 and AIGA ) 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.… 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

Software Systems Development

The Software Systems Development program provides software system developers with the skills needed to design, build, and test systems programs. Learn how to design, build, and test systems programs in C and C++ under the guidance of our dedicated faculty in the Department of Computer Science .

Program Highlights

When you earn your MS in software systems development at Tufts, you'll graduate with diverse and long-term options in the fast-growing industries of systems programming and engineering. Learn how to design, build, and test systems programs in C and C++ through a set of courses containing practical experience in all aspects of software development. Areas of study include: systems programming, program security, software development, systems engineering, and data management.

Choose between thesis and non-thesis degree options to best fit your career goals - the non-thesis program can be completed in as little as one year.

Graduate Cooperative Education (Co-Op) Program

The School of Engineering's Graduate Cooperative Education (Co-Op) Program provides students with the opportunity to apply the theoretical principles they have learned in their coursework to real-world engineering projects. Gain up to six months of full-time work experience, build your resume, and develop a competitive advantage for post-graduation employment.  Learn more about the Co-Op Program .

Career Outcomes

Systems programming is here to stay‚ a complex endeavor requiring human intervention, and it's unlikely to be replaced by artificial intelligence. At Tufts, dedicated professors in the Department of Computer Science will help you get ready for real-world practice at an accelerated rate. With your advanced degree, you'll feel confident managing projects and developing software systems for notable companies like Google and Microsoft.

The software development industry is booming, with a projected job growth of 22 percent in the United States within the next 10 years‚ much faster than the average occupation. As smartphones, tablets, and the applications that make programs accessible to the average consumer continue to integrate into our lives, the demand for software developers will increase.

Careers for graduates include:

  • Front-end developer
  • Mobile engineer
  • Game developer
  • Back-end developer
  • Application developer
  • Tools and enterprise software developer

typing on keyboard.

Application Requirements

Prerequisites for the program include a bachelor's degree and either formal instruction of practical experience in software development, including programming in some high-level language such as Java, C, C++, C# or J#. For those students possessing high-level language experience in a language other than C or C++, Electrical Engineering 200 is recommended as a preparatory course in C.

  • Application Fee
  • Personal Statement
  • Transcripts
  • Three letters of recommendation
  • GRE General Test scores not required for applicants who will have received a degree from an institution located in the U.S. or Canada by time of enrollment. GRE scores required for all other applicants.
  • Official TOEFL, IELTS, or Duolingo test scores (if applicable)
  • Portfolio (optional)

Tuition and Financial Aid

We recognize that attending graduate school involves a significant financial investment. Our team is here to answer your questions about tuition rates and scholarship opportunities .

Please contact us at [email protected] .

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Research/Areas of Interest: data science, software systems engineering, performance analysis, system, network, and data management

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Marty Allen

Research/Areas of Interest: Artificial intelligence, machine learning, reinforcement learning.

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Remco Chang

Research/Areas of Interest: Data visualization, visual analytics, human-computer interaction, databases, computer graphics

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Research/Areas of Interest: cyber security, web engineering

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Lenore Cowen

Research/Areas of Interest: data science, graph algorithms, distributed algorithms, approximate routing, classification and clustering for high-dimensional data, coloring and its generalizations, computational molecular biology

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Ethan Danahy

Research/Areas of Interest: design, implementation, and evaluation of different educational technologies

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J.P. de Ruiter

Research/Areas of Interest: Cognition and Psycholinguistics

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Fahad Dogar

Research/Areas of Interest: Improving performance and reliability of networked systems, specifically cloud-based systems, mobile and wireless systems, and the Internet. Also, interested in designing technologies for developing regions.

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Karen Edwards

Research/Areas of Interest: low-dimensional geometric topology

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Jeffrey Foster

Research/Areas of Interest: Programming languages, software engineering, security

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Soha Hassoun

Research/Areas of Interest: Machine Learning; Systems Biology; Metabolic Engineering, computer-aided design for integrated circuits

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Michael Hughes

Research/Areas of Interest: Machine learning : probabilistic models, Bayesian inference, variational methods, time-series analysis, semi-supervised learning Clinical informatics : electronic health record analysis

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Robert Jacob

Research/Areas of Interest: human-computer interaction, new interaction modes and techniques, implicit brain-computer interfaces, user interface software

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Dave Lillethun

Research/Areas of Interest: computer science education, distributed systems, operating systems, networked systems, software development, secure systems and networking

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Research/Areas of Interest: Data Science, Machine Learning, Bayesian Methods, Deep Learning, Graph

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Noah Mendelsohn

Research/Areas of Interest: distributed systems, operating systems, World Wide Web

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Megan Monroe

Research/Areas of Interest: data, visualization, language

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Raja Sambasivan

Research/Areas of Interest: Cloud computing, evolvability, debugging distributed systems.

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Matthias Scheutz

Research/Areas of Interest: Artificial intelligence, artificial life, cognitive modeling, foundations of cognitive science, human-robot interaction, multi-scale agent-based models, natural language understanding.

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Mark Sheldon

Research/Areas of Interest: programming languages, software systems, concurrency, distributed information systems

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Elaine Short

Research/Areas of Interest: Algorithmic human-robot interaction for robust and socially appropriate assistance to human users, especially users with disabilities.

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Jivko Sinapov

Research/Areas of Interest: Artificial Intelligence, Developmental Robotics, Computational Perception, Robotic Manipulation, Machine Learning, Human-Robot and Human-Computer Interaction

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Donna Slonim

Research/Areas of Interest: data science, algorithms for analysis of biological networks, gene and pathway regulation in human development, algorithms for precision medicine, computational approaches to pharmacogenomics and drug discovery or repositioning

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Diane Souvaine

Research/Areas of Interest: computational geometry, design and analysis of algorithms, computational complexity

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Richard Townsend

Research/Areas of Interest: functional languages, compilers for embedded systems, program analysis and optimization, embedded domain-specific languages

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Daniel Votipka

Research/Areas of Interest: computer security and privacy, secure development, security professionals, human-computer interaction, mobile security

Related Programs

Computer science (certificate), computer science (post-bacc), computer science (online post-bacc certificate), computer science, computer science (online).

Master Thesis

I have extensive experience in supervising (42) and examining (100+) Master Theses in Software Engineering, Software Technology, and Software Development. Below you can find some examples of theses I have supervised as well as thesis topics I am interested in.

However, my interests are broad; if you are a good student don't hesitate to contact me and we can discuss it. If you are not a student with top grades and ambition do not bother; I get very many requests and it is unlikely I can help you.

When at BTH I worked for several years in a project to improve Master Theses in Software Engineering. The processes, supporting documents and lectures as well as rubrics for quality that I developed can be found on this page . If I supervise your thesis you can expect to use this material extensively. You can also expect that the aim is both industrial relevance/effect and academic publication; this gives you the best options for your future career after the thesis.

Thesis Topics

All topics listed below are free (as in not taken by any student) but not everyone has a detailed description online; if you are interested in any of these please email me.

  • Robustness Testing of Deep Learning and Machine Learning Models
  • Optimizing the Diversity and Diameter of Test Sets ( ReTest can support this)
  • Automated Search for Corner Cases for Testing Automotive Systems
  • Testing Software Systems with AI and Machine Learning Components
  • Extending Unit Testing Frameworks for Verification of Robustness Requirements
  • Extending Unit Testing Frameworks for Verification of Performance Requirements
  • Automated Boundary Testing ( ReTest can support this)
  • Selecting Typical Test Cases from a Large and Generated Set ( ReTest can support this)
  • Automated Robustness Testing
  • Group Creativity and Collective Intelligence and its effect on Requirements Engineering
  • Personality of Professional Software Engineers and How it Affects the Organization
  • An Integral Theory of Software Use
  • Measuring and analysing (Non-)Use of Software Engineering Artefacts
  • Similarity Analysis of Product Customization Artefacts
  • A General Framework for Test and Code Optimization based on Change Data
  • Evaluating Fault Location Methods in Industrial Practice
  • High-resolution Software Analytics with Bayesida Data Analysis
  • Statistical Debugging of Dynamic Programming Languages
  • A Mutation Testing Library for Julia
  • Information Theoretical Modeling of Software Development
  • Automated Ranking of SE Venues based on Citations

Master Theses - Supervised

Papers based on master theses.

I always have the goal that master theses I supervise should be published. I will generally help and encourage students to publish if the work is good enough. A large number of papers in my publication list are the results from master thesis projects. The students are always included in a publication based on their thesis project; depending on the level of contribution to the work itself and to the final paper we will decide on author order. A representative sample of such papers can be found below:

  • Publications
  • Presentations

master thesis software development

Department of Computing

Master of Software Development

Fall 2024 priority application deadline: june 30, 2024, program introduction.

The Department of Computing introduces a new Master’s of Software Development program that provides a practical pathway toward learning a current, in-demand skill set with no significant programming experience required.

Our program adopts a hands-on, practical approach to software development, equipping students with industry-ready competencies in coding, problem-solving, and collaboration. It covers programming fundamentals to modern app development practices, all in four semesters from start to finish. Upskill to become qualified for career opportunities in software development that offer increased flexibility, job security, higher income potential, and genuine job satisfaction.

The Master’s of Software Development program is uniquely tailored to complement our new Master’s of User Experience Design program, offering graduates a comprehensive skill set encompassing both development proficiency and design awareness. This interdisciplinary synergy empowers graduates to excel in multifaceted roles, seamlessly integrating design principles with technical implementation. Throughout the program, students engage in collaborative projects and coursework alongside peers from both disciplines.

With a total of 30 credits distributed across four semesters, students can complete the program in a condensed time frame of just 16 months . Additionally, our program stands out for its affordability and accessibility , featuring scholarship opportunities and a hybrid learning model that accommodates both in-person and remote synchronous participation.

master thesis software development

Flexibility for Learners: HyFlex combines the terms “hybrid” and “flexible.” In a HyFlex course, students have the freedom to choose how they participate and can enroll in one of two modalities:

  • Attend face-to-face synchronous class sessions in person (in a classroom).
  • Participate in face-to-face class sessions via video conference.


Bridge the gap between development & design. Our Master’s of Software Development (MSD) program is designed to integrate and work closely with our Master’s of UX Design (MUXD) program through both coursework and real-work projects.

Learn More About MUXD

master thesis software development

Students & Learning

We welcome applicants from diverse backgrounds and skill levels. Our program is structured to embrace pivot learners and individuals seeking to transition into software development from other disciplines.

Our curriculum is focused on teaching project-based, real-world tools and practices that are in high demand across the software industry. Students will gain proficiency in modern technologies and methodologies that are mainstream in the software development field.

  • Bring the skills you have—no significant programming experience is required.
  • Become career-ready by learning the practical skills employers want.
  • Upskill within your current field or pivot into software development.
  • Learn from faculty with extensive industry experience.
  • Collaborate with other graduate students in our UX design program on real-world projects.
  • Qualify for competitive career opportunities in software development.
  • Complete your degree in four semesters over 16 months, in-person or remote.

Curriculum & Faculty

Meet our faculty members to find out who you could mentor with.

View Our Faculty

master thesis software development

Application info

Acceptance into the Master’s of Software Development program will be based on the number of seats available and an evaluation of the following:

  • B.S. or B.A. from a regionally-accredited institution, or equivalent for international students, with corresponding undergraduate transcript(s).
  • 2–3 confidential letters of recommendation.
  • Curriculum vitae/resume.
  • Video submission.

The CV/resume should provide the admissions committee with information about any experiences or skills you have supporting your candidacy for the Software Development graduate program. List your academic and professional work history, any skills related to programming and software development, applicable research methodologies, and technical projects.

As part of the application process, you will be asked to record and submit a 3–4 minute video narrative addressing the following questions to help us learn more about you and your interest in the Master’s of Software Development program.

  • Why do you want to study Software Development?
  • What makes you interested in studying at Utah Tech University?
  • What are your short term and long term career plans?
  • What personal strengths would you bring to the program?
  • Share your experience in programming or software development (if any).
  • Apply through the main Utah Tech University Admissions Application at
  • Apply for graduate school through the Utah Tech University website by clicking on “Apply for Admissions” at the right-hand side of the main page or
  • Create an account if you are a first-time user, or log in if you attended UT in the past two years.
  • On the new page, click on “Graduate Student Application (Master’s Degrees)” or “Start New Application”
  • Fill out the appropriate year you plan to begin attending and fill everything out until the page gives you the chance to submit the following forms as a part of the application.
  • Request official transcripts for all undergraduate and graduate coursework. Utah Tech/DSU undergraduates may request the registrar upload their transcript free of charge by emailing [email protected] .
  • Upload required documents

International Students

All international students and any applicants educated outside the United States must demonstrate proficiency in Standard American English. The following link lists additional information needed to supplement an international application.


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Student Projects and Thesis Topics

Selection of proposals for student projects ("Projekt" for Bachelor, "Praktikum" and "Team-Projekt" for Master) and thesis topics (Bachelor and Master). Please do not hesitate to contact us if you are interested in a project or thesis at the Chair of Software Engineering. If you have your own idea for a project or a thesis topic: Let's talk about it!

Available - Read More…

In progress

Selection of student projects and thesis topics on which students are currently working on. If you find one of the topics interesting please ask the tutor about similar or follow up projects/theses.

In progress - Read More…

Selection of student projects and thesis topics that have already been finished. If you find one of the topics interesting please ask the tutor about similar or follow up projects/theses.

Finished - Read More…

DigitalCommons@Kennesaw State University


Master of Science in Software Engineering Theses

Software engineering represents the fastest growing segment of software professionals, men and women who solve problems and issues in the development of mission-critical software to meet the needs of business and industry. The MS in Software Engineering at Kennesaw State University prepares students for careers in this field by exposing them to real-time strategies and procedures that will give them a competitive edge in the market. All courses in the program are available both face-to-face and online, and students can decide which delivery more is best for them for a particular course.

The program consists of 7 required courses and a number of electives. Students can either take the project option, under which they complete 4 elective courses and a software engineering capstone project, or the thesis option, under which they complete 3 elective courses as well as a thesis. This program is available completely online as well as in the traditional face-to-face mode, or any combination of the two.

Students entering the program must have at least a bachelor's degree. Students who have an undergraduate degree in an area outside of computing can transition into software engineering by completing our foundation courses. Such students may be assigned up to a maximum of 5 foundation courses. Students with a degree in a computing discipline other than software engineering may also be assigned one or two foundation courses based on a review of the student's credentials.

This collection was started with the graduates of the Fall 2015 semester, after the consolidation between Kennesaw State University and Southern Polytechnic State University was final (July 2015).

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Theses/dissertations from 2022 2022.

The Stakeholder-Profile Framework for Tacit Knowledge Acquisition in Requirements Elicitation Interviews , Rasha Eltigani

A Comparative Study on Blockchain-based Electronic Health Record Systems: Performance, Privacy, and Security Between Hyperledger Fabric and Ethereum Frameworks , Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero, and Xia Li

Theses/Dissertations from 2021 2021

Decentralized Aggregation Design and Study of Federated Learning , Venkata Naga Surya Sameeraja Malladi

Federated Learning for Secure Sensor Cloud , Viraaji Mothukuri

Theses/Dissertations from 2020 2020

A Preliminary Analysis of how a Software Organization’s Maturity and Size Affect its Intellectual Property Portfolio , Daniel Gifford

Theses/Dissertations from 2019 2019


Theses/Dissertations from 2017 2017

Feasibility of Using Virtual Reality in Requirements Elicitation Process , Aman Bhimani

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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 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. 


Eshaan Pandey

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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Master Thesis Software Engineering Projects

                 Master Thesis Software Engineering Projects is our world’s leading project provider that continuously working on self-improvement by our true professionals. This means that we staying aware of latest software trends and acquiring knowledge with keep horseracing the high tide. To obtain your PhD degree, a student must complete the thesis. This differs from the university/institution- each of which contains the set of guidelines for writing this.

Let’s take a look at our software engineering projects

                –”Software engineering is a continuously growing research field for inventing new tools, ideas, methods, technologies. The upcoming development in the software engineering research field of big data, network security, software engineering project management, android computing, cloud computing, etc.” 

We offer software engineering projects in an affordable price and given opportunity collaborate with us. There are many ways for you to communicating with us, including Team viewer, Skype, Video call, Audio files, Phone calls, Email etc.

Recent Trends in Software Engineering

  • Agile Software Development
  • Applied mobility
  • Clouds capability
  • Real analytics
  • Social computing
  • Continuous integration
  • Automotive applications
  • Service design
  • Mobile apps
  • Big data analysis
  • Augmented reality
  • Functional programming
  • Security demand increasing
  • IoT Development
  • Platform independent frameworks
  • Social goods and Data science
  • Workplace, and Micro services
  • Machine learning and artificial intelligence

Software Engineering Projects

                 Master Thesis Software Engineering Projects gifts for students to involve with our research community also for their projects. Students have an opportunity to strongly connect with us to discuss their ideas for a project.  We offer a dynamic and also peaceful technological environment to start work in deep and have a chance to participate in our teaching sessions, seminar programs, and workshops, etc. After your project completion, start to work with your dissertation/thesis/final reports –it progresses with our top technical writers, and if it ready, we also deliver you before your deadline.

To succeed, jump as quickly at opportunities as you do at conclusions………… -Benjamin Franklin

Advanced Concepts in Software Engineering

  • Design pattern and also agent based simulation
  • Software Repository Mining
  • Unit Testing Metrics
  • Micro service architecture of fault tolerance
  • Reliability: Clouds systems engineering
  • Infrastructure deployment and also in modeling
  • Mobile web apps not web sites
  • Architectural paradigms for IoT
  • Technical Dept Repayment
  • Automatic configuration optimization
  • Tools for code quality management
  • Machine learning/artificial intelligence exclude big data
  • Software systems assessment also through software fault injection
  • Trivial mutant equivalences detection also through compiler optimizations

Development Tools and Software’s

  • RISE Editor
  • MetaCASE tool
  • Microsoft Visio
  • KATALON Studio
  • Parasoft SOAtes
  • Spark Systems
  • Dreamweaver

Purpose of Tools and Software’s

  • ECO: Engineering change order software platform to support domain driven design also for maximize the object relational mapping and UM modeling.          
  • Apache ANT: Conventional software engineering tool implemented in java that also used to design patterns.
  • CASE tools: Set of software to that also used to development software projects and applications.
  • RISE Editor: Open source free information modeling tool/model driven engineering tool also for information system development.
  • MetaCASE tool: Application software that provides functionality also to create one or more applications.
  • Microsoft Visio: Software that easy-to-use, import and export and extensive shape libraries under Linux, Mac, and also Windows environments.
  • ER/Studio: Database design and also data architecture software used in forward and reverse re-engineering.
  • Star UML: Diagramming software that also used to draw 9 set of UML diagrams implemented in C, C++ and java
  • Argo UML: Diagramming application software written in java. It is also used in reverse engineering
  • JBuilder: Integrated Development Environment (IDE) used in software middleware and also engineering applications.
  • JMeter: Open source software application purely written in java that also used to designed load test behavior and measure performance.
  • Tigris: Dedicated for open source software engineering tools and it provides information resources also for software engineering
  • KATALON Studio: Most powerful and also simple automation software solution for software engineering and testing
  • MODELIO: Open source BPMN and UML modeling tool that used for reverse engineering, code generation and also new languages development (SoaML, SysML etc.)
  • Parasoft SOAtes: World’s leading enterprise grade solution for API testing and integrity and it is used for business and also security based critical applications.
  • Spark Systems: Enterprise architect and also design tool based on UML that used for visual modeling
  • Dreamweaver: Web application software that used also for the server-side scripting languages like HTML, CSS, and also ASP.NET.

Major Research Topics in Software Engineering

  • Future complex systems design
  • Decision making improvement, economics and also evolutions
  • Dependable software-intensive systems creation
  • Resource and also confident estimation
  • Adaptive system emerging system also classes development
  • Rethinking software production
  • Complexity, security and also in distributed aspects
  • Adaptively and also dependability
  • Technology development also for early life cycle steps
  • Quality and also efficiency of software production

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