I am interested in program analysis of software from the data science domain to identify possible errors in, for example, R programs. To analyze data science programs, I am exploring the usage of abstract interpretation for data science software to automatically infer code constraints for certain program aspects by soundly abstracting the concrete semantics of the program. Furthermore, I am interested in linting data science code to statically identify code smells and potential bugs in data science code. To this end, I am working together with Florian Sihler on flowR, an open-source static code analyzer for the R programming language. Besides my research, I assist in teaching in the course “Aktuelle Themen der Softwaretechnik aus Forschung und Praxis” in the winter term 2025.

Publications