Externally Funded Projects
This page lists summaries of current and past projects funded by third parties of which I was Principle Investigator (PI). Overall, I raised about 900,000 Euro in third party funds so far.
KI4ALL – Interdisziplinary teaching of data-centric method and application competences (2021-ongoing)
Funded by the BMBF for four years
Artificial intelligence (AI) is everywhere and quickly becoming a standard method for solving problems with data. Within this project, we develop new and enhance existing teaching material for AI for everyone to use. We follow an interdisziplinary approach, in which we also produce materials for teaching AI in different domains, e.g. health care, transport, or engineering.
This project is a joint project of the TU Clausthal, the TU Braunschweig, and the Ostfalia HAWK.
DEFECTS – Comparable and Externally Valid Software Defect Prediction (2018-ongoing)
The comparability and reproducibility of empirical software engineering research is, for the most part, an open problem. This statement holds true for the field of software defect prediction. Within this project, we create a solid foundation for comparable and externally valid defect prediction research. Our approach rests on three pillars. The first pillar is the quality of the data we use for defect prediction experiments. The current studies on data quality do not cover the impact of mislabeled data. The second pillar is the replication of the current state of the art. The third pillar are guidelines for defect prediction research. In case we cannot get researchers to avoid anti-patterns that led to bad validity of results, our efforts to combat the replication crisis of defect prediction research will only have a short-term effect. To make our results sustainable, we will work together with the defect prediction community to define guidelines that allow researchers to conduct their defect prediction experiments in such a way that we hopefully never face such problems with replicability again.
GAIUS – Maintenance activities for the sustainability of AUGUSTUS (2018-2022)
AUGUSTUS is a tool for the structural annotation of genes in genomic sequences. Within this joint project with Prof. Dr. Mario Stanke from the University of Greifswald, we will work on the maintenance of AUGUSTUS. While the prediction methods of AUGUSTUS were advanced over the years, the maintainability and sustainability. This is highlighted by usability issues, but also general issues within the codebase. This project will focus solely on the maintenance of AUGUSTUS to improve upon this, i.e., improve the usability of AUGUSTUS, as well as the maintainability of the codebase.
Pilot Study: Defect Prediction at Continental (April 2017-December 2017)
Funded by the Continental GmbH
SmartSHARK is a versatile tool for software repository mining. Within this project, we performed a pilot study in cooperation with the Continental GmbH to assess potential benefits of using SmartSHARK for defect prediction of C and C++ software developed in-house at Continental.