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Faculty of Mathematics and Natural Sciences

Abteilung für Informatik

Research

Our leading research objective:
Help engineers understand how software-intensive systems will behave in reality

We are actively doing reserach in the areas Requirements Engineering, Software Engineering & Machine Learning, Explainable Intelligent Systems, Research Software Engineering, Data-driven Systems Engineering and Model-based Systems Engineering. Almost each area is leaded by one of our team members.

Software Engineering & Machine Learning

Adapt the SE process to the new challenges of ML & utilize ML to improve SE.

Researcher: All members of SSE

  • Requirements Engineering for ML Applications (paper)

Requirements Engineering

Automate RE as far as possible.
Researcher: Prof. Dr. Andreas Vogelsang

  • Automatic Requirements Classification (paper)
  • Automatic Trace Link Recovery (paper)
  • Automatic Glossary Term Extraction (paper)
  • Automatic Test Case Derivation from Natural Language Requirements (paper)
  • Automatic Risk Prediction (paper)

Explainable Intelligent Systems

Explain intelligent and autonomous behavior to users.

Researcher: Dr. Mersedeh Sadeghi

  • Explainable System Requirement
  • Explainable Modeling
  • Software Engineering of Explainable systems
  • Explainability and Ethics
  • Development of (explainable) cyber-physical, IoT and autonomous systems in our SmartLab

Research Software Engineering

Improve development of research software.
Researcher: Adrian Bajraktari
(this topic is new, therefore there are no publications yet. If you are interested or have an idea for work in this area, please contact us!)

  • Code Quality and Principles
  • Process and Team
  • Validity and Reproducibility
  • Credibility and Acknowledgement

Data-driven Systems Engineering

Improve SE by collecting and analyzing runtime data.

Researcher: Patrick Ebel

  • Integrate NL Requirements with System Executions (paper)
  • Analyze Feature Usage based on Interaction Data (paper)

Model-based Systems Engineering

Improve MBSE adoption in practice.
Researcher: Dr. Tiago Amorim

  • SPES Modeling Framework (paper)
  • Feature Dependency Analysis (paper)
  • Drivers and Hurdles of MBSE Adoption (paper)
  • MBSE Adoption Strategies and Best Practices (paper)
  • MBSE Maturity Model (paper)
  • Decision Support for Process Maturity Improvement in MBSE (paper)