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The research efforts of the faculty of Computer Science are organized in four research lines.

  • software quality
  • security and privacy
  • artificial intelligence
  • teaching and learning

Below you find a brief description of these lines and the main themes the research addresses. Read more on these research lines, the teams, the projects and the publications in the Research programme Computer Science 2020-2025: Towards high-quality and intelligent software.

Software quality

Software failures have far-reaching implications in terms of money, safety, privacy, etc. Hence, guaranteeing the quality of software is increasingly important. Unfortunately, this does not always happen in practice, and some already go as far as arguing that there are signs of a ‘coming software apocalypse’. This research line focuses on quality assurance techniques related to software testing as well as formal methods. The two main themes in this line are:

  • Software testing
    Scriptless test automation, early shift-left testing
  • Formal methods
    A unique research program towards formal methods for the masses, both in terms of users and impact. More specifically the focus is on: Formal methods for standard libraries, Formal methods for concurrency, Formal methods for binaries and Formal Resource Consumption Analysis.

Security and privacy

Security and privacy are crucial to be constantly investigated and improved “in a world where everything is a computer". The research addresses security and privacy of software, computer systems, and information systems. The focus is on:

  • Applied cryptography for security and privacy
  • AI for security
  • Digital fingerprinting
  • Formal methods for security
  • Software tools to support security education
  • Societal relevance: relation with the KIA Veiligheid

Artificial intelligence

National and European research agendas in Artificial Intelligence strongly promote both technical advances (such as deep learning) and societal challenges to be tackled (such as the ethical study of consequences of AI technology). The department of Computer Sciences is actively involved in both lines of research, and both applied and academically. In addition, the AI team is developing education in AI, including a new master program. The activities are focused in the following directions:

  • Trustworthy artificial intelligence
  • AI in practice

Teaching and learning

This research line consists of five themes.

  • Software technology for learning and teaching
    How can techniques from Software Technology (ST) and Programming Languages (PL) be used for designing and building tools for education. How to automatically generate hints and feedback for such tools.
  • Computing education
    This research concerns content specific pedagogy (Dutch: vakdidactiek) for computer science and related areas such as digital literacy, in particular computational thinking. Teaching and learning of specific content (i.e., concepts or practices) is investigated:
    - goals and objectives connected to this content
    - students’ understanding of this content
    - instructional strategies for teaching this content
    - assessment connected to this content.
  • Scaffolding in Software Engineering
    Software Engineering involves several complex tasks, for which students need to acquire both conceptual and procedural knowledge. In this theme student support in the form of procedural guidance as an instructional strategy is studied.
  • Programming Education
    Code quality is considered an important aspect of programming. In this research is investigated which criteria for code quality are suitable for teaching novice programmers. What are students’ perceptions of code quality and what are the stages they go through while learning about this. Instruments for assessing code quality are developed and tested, as well as the application of these as tools for formative assessment, both for teacher feedback and for peer review of students’ program code.
  • Computational Thinking
    The term Computational Thinking refers to a set of problem-solving skills that make use of concepts and methods stemming from computer science. We investigate students’ understanding and instructional strategies for Computational Thinking, especially with respect to abstraction skills of primary school students. Special attention is given to teachers’ knowledge and skills required for incorporating Computational Thinking in their lessons.

Read more on these research line, the team working on each line, the projects and the publications in the Research programme Computer Science 2020-2025.