master thesis software development

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 (TOPIC AREAs, INDUSTRIAL COLLABORATION)

(TOPIC AREA)

(PROJECTS)

(TOPIC AREA)

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

Programming

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.

List of Software Engineer Research Topics in 2024

Here is a list of Software Engineer research topics:

Artificial Intelligence and Software Engineering
Natural Language Processing
Applications of Data Mining in Software Engineering
Data Modeling
Verification and Validation
Software Project Management
Software Quality
Software Models

1. Artificial Intelligence and Software Engineering

a. 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.

b. 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

a. 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.

b. Efficiency

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

a. 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.

b. 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)

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.

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.

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

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:

Statistics for papers based on Theses
Type	Statistic
Chance of paper from finished M.T. project	43.5% (10 of 23)
Papers per project (overall)	0.5 (13 of 26)
Papers per project with at least one paper	1.3 (13 in 10)

Publications
Presentations

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 work with 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 .

Program 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 25 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

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.
Reading: 26
Listening: 26
Writing: 22
Speaking: 25
Minimum of 7.0 for each subscore
Literacy: 125
Conversation: 120
Comprehension: 135
Production: 105
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] .

Career Outcomes

Typing on a laptop with code displayed on the screen

Average Salary: $130K+

Projected Job Growth (2022-2032): 25%

*Sources: Average salary and projected job growth statistics are from the U.S. Bureau of Labor Statistics Occupational Outlook Handbook.

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

Marty Allen

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

Remco Chang

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

Research/Areas of Interest: cyber security, web engineering

Lenore Cowen

Research/Areas of Interest: computational molecular biology, data science, graph algorithms, network science, discrete mathematics

Ethan Danahy

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

J.P. de Ruiter

Research/Areas of Interest: Cognition and Psycholinguistics

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.

Karen Edwards

Research/Areas of Interest: low-dimensional geometric topology

Jeffrey Foster

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

Soha Hassoun

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

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

Robert Jacob

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

Dave Lillethun

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

Research/Areas of Interest: Machine Learning, Data Science, Deep Learning, Generative Models, Time Series, Graph Learning

Noah Mendelsohn

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

Megan Monroe

Research/Areas of Interest: data, visualization, language

Raja Sambasivan

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

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.

Mark Sheldon

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

Elaine Short

Research/Areas of Interest: human-robot interaction, accessibility, robotics, human-in-the-loop machine learning, assistive technology

Jivko Sinapov

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

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

Diane Souvaine

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

Richard Townsend

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

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).

Bibliography
More Referencing guides Blog Automated transliteration Relevant bibliographies by topics
Automated transliteration
Relevant bibliographies by topics
Referencing guides

Master thesis: Potential analysis of software development with low code platforms in public administration

This master’s thesis examines the potential of low-code platforms for software development in public administration. For this purpose, an empirical study was conducted on the basis of expert interviews in order to identify the advantages, prerequisites and challenges of the use of low code platforms. The analysis is based on the example of the low code platform A12 from mgm technology partners and its relevance in the context of OZG implementation. The work provides an understanding of the topics “digitization in public administration”, “software development” and “low code platforms”.

Short & concise

The master thesis highlights the potential of low code platforms for software development in public administration.
Possible application areas for the use of low code platforms in public administration include business process management or artificial intelligence.
Result: With the software development in the public administration there is no challenge, which is too complex, in order to convert it with a Low code platform.

The interview partners come from various fields and positions, including project managers, experts from public administrations, administrators and software developers. They provide interesting insights into the software development process and the fulfillment of the promise of low code platforms to reduce programming effort.

What problems do low code platforms solve?

In a nutshell, low-code platforms have a positive impact on the following factors:

Time savings: developers* can build applications faster by leveraging existing templates and using simple drag-and-drop functionality.
Cost savings: Since less code needs to be written manually, development costs can be reduced.
Increased efficiency: Low-code platforms provide an intuitive user interface and a high level of clarity, which increases the efficiency and reliability of application development.
Increased agility: Changes and customizations can be implemented faster because less code needs to be written manually.
Shortened time-to-market: low-code platforms enable applications to be developed and deployed faster, resulting in a shortened time-to-market.
Increased accessibility: Low code platforms enable non-developers to create simple applications, which increases accessibility to application development.
Risk reduction: Low code platforms reduce the risk of shadow IT, cyberattacks and other threats by making it easier to build compliant and secure applications.

Challenges of software development with low-code platforms in public administration

Low code platforms can change the static, traditional approach in public administration because they encourage an agile approach and not everything has to be perfectly planned at the beginning of the project. This requires a different approach to digitization projects on many levels. One challenge is building trust between the authority and the service provider, which is crucial for successful projects. Low-code platforms enable the rapid deployment of visual solutions and can involve users directly in application design. One clear finding of the research is that when it comes to software development in public administration, there is no challenge that is too complex to implement using a low code platform.

Possibilities for expanding the area of application of low-code platforms in public administration

In order for the area of application of low code platforms in public administration to expand, greater support for the software development process is necessary. This is possible if the first prototypes of the software can be tested more quickly and users know what the operating, testing and development environment looks like. For the broader use of low-code platforms, there should ideally be the possibility to overview the processes and environments of software development and to optimize them if necessary. At best, this can also optimize the operational flow.

Future potential application areas for the use of low code platforms in public administration include

1. Business process management

As a future possible application area, the field of business process management for specialized procedures in public administration offers great potential. This makes it possible to digitize not only a subarea, but complete processes with the help of low code platforms. Thus, all tasks in a workflow are visible and allow to identify potentials and bottlenecks in the processes. The visibility of the processes makes it possible to react dynamically to capacity bottlenecks.

2. Artificial Intelligence

Another application area is artificial intelligence that builds applications via voice interface. Low code platforms offer a huge potential due to the standardization, because not only user interfaces can be developed, but also the complete backend is integrated. Thus, it is much easier for AI to build new applications, revert to existing building blocks and then reuse them.

Low code platforms have the potential to address the skills shortage in the IT industry and can help improve IT security. These platforms allow subject matter experts to develop their own software without having to be familiar with the technical systems in the background. This means that misunderstandings can be avoided during requirements elicitation and development time can be shortened. They also offer greater software usability and the ability to gather direct user feedback. Low code platforms, through their modular approach, have the potential to speed up software development, make application maintenance easier and reduce the need for traditional development effort. They are particularly well-suited for projects where a working application does not exist at the outset or where customizations are required frequently. However, it is important to identify challenges in software development in public administration in order to eliminate potential problems in time and make the most of the potential of low-code platforms.

Further information:

Download the master thesis by Jonas Baur (in german only)

Internal vs. external GenAI projects: A decision guide for companies

Scale AI Deep Dive Day: Workshop on the future of sales in the insurance industry

AI and Flight Levels: How to get your AI turbo on the road

mgm consulting partners Holländischer Brook 2 20457 Hamburg Tel +49 40 / 808 128 20-0 Email [email protected] Locations & Contact

mgm insights LinkedIn kununu

Department of Computing

Master of Software Development

Fall 2024 application deadline: july 31, 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.

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.

Collaboration

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

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

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.utahtech.edu
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 https://apply.utahtech.edu/apply/
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.

INTERNATIONAL GRADUATE STUDENT ADMISSIONS

Joe Francom

Department chair, computing.

Email: [email protected]

Phone: 435-652-7732

Office: BNO 237

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…

August
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Master’s Thesis

Preliminary Note: According to the Master regulations, the final paper in the Master program in Computer Science is the Master’s Thesis.

In a Master’s Thesis, candidates show their ability to independently perform scientific research on an appropriately challenging theme that also gives them the opportunity to develop their own ideas. On the basis of the "state-of-the-art" processes, the students must systematically apply the methods of computer science.

The Master’s Thesis must be written in the student's specialization area. The thesis advisor ensures that the objectives of the thesis can be reached within the intended time period. Advisors are available for consultation throughout the entire development of the thesis. They should regularly check that the work is progressing well and should also counteract any potentially negative developments, such as the student not meeting the objectives or exceeding the given time limit. They also give timely advice when the student is writing the thesis, and before the student submits the completed thesis.

All candidates must report the starting date of a Master’s Thesis to the Examination Office; the thesis topic and the starting date of the official processing period are then documented by the thesis advisor and forwarded to the Examination Office. The knowledge required for the thesis and how to acquire this knowledge should be clarified prior to when the topic is granted. For a Master’s Thesis, graduate students are first formally obliged to design a work plan. Approximately one month of full-time work (5 ECTS) is intended for this starting phase. The work plan (called a “Proposal”) must explore the thesis topic thoroughly enough and lay out a detailed plan for the following research on the thesis topic. The Proposal must explain this proposed research through detailed contents and depth as well as a complete depiction of the considered aspects. The Proposal must contain the following elements: a description of the task to be completed, the reasons behind working on the thesis, a clear formulation of the objectives, a description of the work necessary to reach the goal, and an accompanying timetable and preliminary outline of the written thesis. The work plan must be countersigned by the thesis advisor and submitted for approval to the Examination Office together with the application for the Master's Thesis. From this point on, the planned processing time is five months, whereas the start of the processing period agreed upon with the thesis advisor takes the one-month processing period for the work plan into account.

The written thesis is the main component of the final research. It should contain an incisive, understandable description of the completed research task, the research results, and the approach used to reach the result. In a thesis, candidates must also justify their decisions on which research methods or alternative solution approaches were used. The Master's Thesis must be written in the style of a scientific treatise. This includes in particular a summary, an outline, a description of the "state-of-the-art", and a bibliography of the literature used for the thesis. If software was designed and implemented during the thesis research, the structure, work methods and interfaces of the software must also be described precisely. Although it is not necessary to include the software documents in the written thesis, the software system, including the source code, must be available to the thesis advisor for review. Candidates must submit the written thesis in print to the examination office. Their advisor receives an additional copy in a common electronic format (PDF).

The thesis defense, meaning an open-audience presentation followed by scientific discussion, is also an element of the Master’s Thesis. During the defense, the candidate must explain his/her research results concisely in a 30- to 45-minute presentation and then answer questions posed by a professional audience (usually during an advanced seminar held by the advisor). Ideally, the defense should be held soon after submission of the thesis.

To determine the grade granted for the thesis, the various achievements presented in the thesis are evaluated individually and internally. In general, the following individual achievements are divided into the categories listed below, arranged from the top down in order of the grade-relevant importance of the individual aspects.

Research Results . The results of the research work are given the highest priority and can come in various forms: theorems, software products, hardware products, empirically derived statements, or a mixture thereof. The approach employed to reach the results are also evaluated when the quality of the results are assessed.

Written Thesis. The written thesis, the main component of the research work, is given second priority. Here the evaluation includes determining how understandably graduates present the findings and research method to expert readers, and how well they concentrated on essential details and excluded non-essential details. The form, graphics, language and style of the thesis are also assessed.

Work method . The evaluation of the work method includes determining how purposefully and independently the candidate performed the research.

Presentation and discussion. Here, the committee evaluates the preparation of the presentation, the visual aids used for the presentation (such as slides), the candidates’ rhetorical skills and their ability to handle critical questions.

Due to the nature of the field of computer science, a Master’s Thesis that is written in cooperation with other institutes or (industrial) university-external parties is no rarity. And sometimes candidates write their thesis on a topic at an institute that corresponds to their minor subject. In both of these cases, the thesis advisor must inspect the research topic carefully and ensure that the candidate is given competent "on-site support". If the Master’s Thesis is written in a minor subject and an advisor in this minor subject takes on the role of the candidate’s supervisor, a university instructor in the Computer Science Department at the University of Paderborn must first determine that the research topic is plausible, and this instructor must supervise the thesis together with the advisor in the minor subject. Merely including the Computer Science Department advisor’s name as the secondary advisor when submitting the completed written thesis is not sufficient.

If the Master’s Thesis is written outside the university, such as at an external company, the thesis advisor must ensure that the candidate is not negatively affected by company-internal constraints (deadlines, financial dependence, non-disclosure agreements for concealing trade secrets). In this sense, “freedom of education” must be guaranteed. Companies are notified that the research work (the written thesis) is, by general rule, open to all readers. In special cases (such as when a patent is pending), a certain limited time period between the end of the research and the actual publication of the thesis can be determined. The in-company advisor/reviewer must make the entire research work available.

When submitting the thesis, candidates pledge to archive a public copy of the thesis for up to at least 5 years. The Computer Science Department, meaning the university in general, does not archive the submitted, accepted written thesis.

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Proposal for master thesis in software engineering

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How to evaluate a software implementation for master thesis

I have developed a software to meet a specific requirement in a research field. There is only one such software developed so far, mine is second.

In the thesis, I explain the implementation of the software. However, I feel like I also need a "Results" chapter. Most of the master theseses I have gone through from various disciplines have such a chapter. Looks like it is a must.

My software generates tangible models, storing a specific information, to be manufactured with various methods, such as CNC or 3D printing.

Output of the software should be considered as results. However, I don't want to conduct a cheesy case study with a bunch of people and publish it as a scientific result. An extensive, thorough study is takes more than 6 months and neither I have that much time nor the the knowledge/experience to conduct such a case study.

For example a friend of my implemented a software for twitter clustering and analyzing. The results are quite straightforward with his software. Run the tool, get the results and interpret them. Done.

I am not sure how to evaluate the results. Models are manufactured successfully, whereas that does not look like a result to me.

How would you approach this question for a possible solution? What my alternatives can be?

1 In computer science, it is indeed typical to have an evaluation/validation section in a master's thesis, but there is no need for this section to be named "Results". You can choose a name that fits best. – lighthouse keeper Commented Jan 12, 2017 at 11:30
4 The "cheesy case study with a bunch of people", as you call it, is often a valuable part of the thesis in that it shows that you are not only capable of coding, but also of designing the material and setting for such a study. The point is not to generate a full-fledged "scientific result", but to show that you could generate such a result if given sufficient funding and time. Furthermore, while a thorough, statistical analysis is beyond what you can do in a Master thesis, do not underestimate the impact of listing at least some "first impressions" uttered by users other than yourself. – O. R. Mapper Commented Jan 12, 2017 at 11:33

2 Answers 2

The goal of your thesis was to create a tool that meets certain requirements. Consequently, your evaluation should show that your tool satisfies these requirements .

One way to organize your thesis is to have a section called "Requirements", where you walk through all requirements detailedly. For example, you could have following requirement with sub-requirements:

R1.1: Brown cats : the model generation works for brown cats
R1.2: Black cats : the model generation works for black cats
R1.3: Checkered cats : the model generation works for checkered cats

Then you have another section called "Validation" where you walk through the requirements a second time, this time discussing for each requirement how you satisfied it.

R1.1 : for 4 sample cats, the tool was able to produce a model (see Fig. 1)
R1.2 : for 5 sample cats, the tool was able to produce a model (see Fig. 2)
R1.3 : for 3 sample cats, the tool was able to produce a model (see Fig. 3)

1 Thank you so much. That sounds reasonable and clarifies the questions – user1449456 Commented Jan 12, 2017 at 11:24

If someone asked you: "does your software work"? How would you prove to them that it does? How did you test the software and proved to yourself that the software works as intended? That could be the basis of a results section.

So, manufactured tangibles through software can be considered as results? – user1449456 Commented Jan 12, 2017 at 11:21

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M.Tech/Ph.D Thesis Help in Chandigarh | Thesis Guidance in Chandigarh

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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:

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.

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.

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.

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.

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.

Click the following link to download Latest Thesis and Research Topics in Software Engineering

Latest Thesis and Research Topics in Software Engineering(PdF)

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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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PDF Master thesis in software engineering and management
Master thesis in software engineering and management A Rationale Focused Software Architecture Documentation method (RFSAD) Muhammad Asad Javed Göteborg, Sweden 2007. 2 ... Software architecture plays a vital role in software development, and so does software architecture documentation. Practitioners have been documenting architectures for many
PDF Agile Project Management in Large Scale Software Development
software development needs, on critical solutions. The studies in the course "INF 5181 - Process improvement and agile methods in software ... discussion in her master thesis is relevant to the communication and trust on global level and is mostly based on literature reviews and semi structured interview. So, I have decided to use more
Offered MSc Thesis topics
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. ... Software development in non-ICT contexts (TOPIC AREA) Creatively self-adaptive software architectures (TOPIC AREA) Continuous experimentation ...
Top 10 Software Engineer Research Topics for 2024
List of Software Engineer Research Topics in 2024. Here is a list of Software Engineer research topics: Artificial Intelligence and Software Engineering. Natural Language Processing. Applications of Data Mining in Software Engineering. Data Modeling. Verification and Validation. Software Project Management.
PDF Design and Implementation of A Software Development Process Measurement
I certify that this thesis satisfies all the requirements as a thesis for the degree of Master of Science. _____ Prof. Dr. Mübeccel Demirekler Head of Department This is to certify that we have read this thesis and that in our opinion it is fully adequate, in scope and quality, as a thesis for the degree of Master of Science. _____
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 ...
What are the latest thesis topics in the area of Software Engineering
University of Duhok. Dear Taha Khamis, There are many hot research topics in software engineering. For example, you may look at the following two topics: 1- Software fault localization: https ...
Software Systems 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
PDF Master's Thesis Simulation Aided Product Software Development
This work is a study of simulation environments as tools for product software development from architecture definition phase to testing the actual end product software code. The purpose of the work was to find a feasible way to utilize simulation environments for improving product time to market. The work was initiated to renew the existing ...
Dissertations / Theses: 'Masters in Software Engineering ...
This masters thesis is about how to enhance creativity and investigates the design process of interaction designers, in terms of the creative process, design support tools and especcially through a concept presented in this thesis. ... Agile software development (ASD) is another major paradigm, which also has been widely adopted by the industry ...
PDF Master Thesis in IT Management EIK034
This master thesis is written in part as a fulfillment to the master program in IT Management, School of Business, Society, and Engineering, Mälardalen University, Västerås, Sweden. ... Software Development (ASD), Dynamic System Development Method (DSDM), Feature Driven Development, and Scrum (Akhtar et al, 2010; Rising & Janoff, 2000).
Dissertations / Theses: 'Software engineering'
In this thesis, I present the Model of Regulation as a new and complementary theoretical model of collaboration for software engineering and showcase its potential by using the model to analyze features of a collaborative tool, gain insights into an open-source software development community and to create an instrument that investigates about ...
Master thesis: Potential analysis of software development with low code
This master's thesis examines the potential of low-code platforms for software development in public administration. For this purpose, an empirical study was conducted on the basis of expert interviews in order to identify the advantages, prerequisites and challenges of the use of low code platforms.
Master of Software Development
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 ...
Student Projects and Thesis Topics
Available. 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 ...
PDF Master'S Thesis a Systematic Literature Review on Agile Project ...
ecent years, it constitutes an interesting and comprehensive research topic.This thesis presents a systematic literature rev. ew (SLR) of published research articles concerning agile project management. Based on a predefined search strategy. 273 such articles were identified, of which 44 were included in the.
Master Thesis
1. Goals. In a Master's Thesis, candidates show their ability to independently perform scientific research on an appropriately challenging theme that also gives them the opportunity to develop their own ideas. On the basis of the "state-of-the-art" processes, the students must systematically apply the methods of computer science. 2.
Some Frequent Writing Tips I Give Software Engineering Thesis Students
In formal texts, such as a paper or thesis report, you want to stay away from informal language of all sorts. This includes word contractions ("don't", "isn't"), but also influences your choice of words and style. When in doubt, go for a more formal style in your report. Active voice is ok (even preferred).
Proposal for master thesis in software engineering
In today's software development organizations, methods and tools are employed that frequently lack sufficient evidence regarding their suitability, limits, qualities, costs, and associated risks. ... Proposal for Master Thesis in Software Engineering Basic information Student 1 Name and P.Nr.: Patrick Seidler, 811223-3377 Student 2 Name and P ...
How to evaluate a software implementation for master thesis
One way to organize your thesis is to have a section called "Requirements", where you walk through all requirements detailedly. For example, you could have following requirement with sub-requirements: R1: Generate 3D cat models: the tool can generate 3D models from 2D cat images. R1.1: Brown cats: the model generation works for brown cats.
Latest Thesis and Research Topics in Software Engineering
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. SDLC or Software Development Lifecycle is a set of stages followed for the development of a software product.
Master
Master_Thesis_Influence of Big Data on Software Development and Business Innovation - Free download as PDF File (.pdf), Text File (.txt) or read online for free. The document discusses the motivation and challenges around big data adoption and innovation in software development and business. It notes that software development is increasingly influenced by new technologies like cloud computing ...
Master Thesis (Software Engineering Projects) Research
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.