TU Graz focuses the automation of diagnosis and testing based on models, and on providing means for risk assessment.
The Graz University of Technology (TU Graz) founded 1811 by Archduke Johann has always been passionate about shaping the future, attracting the brightest minds, creating outstanding conditions for high-quality research and teaching, as well as being a strong partner in national and international cooperation. The Institute for Software Technology has been contributing to this passion focusing not only on Software Engineering but also Artificial Intelligence and Theoretical Computer Science.
The Institute for Software Technology was founded in 2003, comprising today 4 full professors, 4 associate professors, 9 assistant professors, and more than 30 researchers that working on projects funded externally. Members of the institute publish more than 100 peer-reviewed papers on average every year. The institute is committed to highest quality research and teaching, and closely collaborates not only with academia but also with companies aiming at bringing foundational research into practice. Since its beginnings the institute has been carrying out more than 70 applied and foundational research projects. Currently the Institute for Software Technology is hosting the Christian Doppler Laboratory for Quality Assurance Methodologies of Autonomous Cyber-Physical Systems.
Regarding research activities, the Institute of Software Technology is concerned with the theoretical, practical and applied aspects of software engineering. Research lies in the field of intelligent systems, formal verification and systematic testing of software, artificial intelligence, requirements engineering, recommender systems, optimization of industrial problems, game theory, agile software development processes, computer science education, and autonomous robots.
- Coming up with tools and techniques for model-based diagnosis to be used in an industrial context
- Working on means for verification and testing of fault detection systems based on various techniques like combinatorial testing or model-based testing.
- Providing a risk framework when introducing monitoring and diagnosis in actuators and propulsion systems