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Before joining Prof. Pretschner's chair in July 2019, I worked in several positions as software and machine learning engineer. My research focus is on software testing in general and more precisely on regression test optimization in continuous integration environments.

Thesis Supervision

If you are interested in working with us, have a look at our theses openings page or at my currently open topics below (I try to keep them up-to-date).

I am looking for students with a strong background in programming (Java, C/C++, Rust) and high motivation to dig deep into regression testing, dynamic/static code analysis, compiler infrastructure, and continuous integration.

In case you have an interesting idea referring to my research areas, please feel free to contact me directly!

▌ Open  
No topics  
▌ Ongoing  
Regression Test Selection for Rust (with RW) Guided Research
▌ Finished  
Practical Application of Flaky Test Identification and Classification for Root Cause Analysis in the Context of Continuous Integration (with CJ) Master
Detecting Flaky Tests by Comparing Program Traces (with FL) Bachelor
Dependency Injection Aware Regression Test Selection Bachelor
Determining Root Causes of Flaky Tests Using System Call Analysis (with FL) Master
Regression Test Selection for End-to-end Testing in Distributed Multi-language Web Applications Master
Spotting Unsafety in the Wild - An Analysis of Regression Test Selection Tools for the JVM Seminar
Regression Test Optimization in Microservices by Linking Distributed Tracing with Code Instrumentation Master
Configuration of Static Analysis Tools for Effective Bug Detection (with Itestra and MS) Master
Test Suite Composition of Open Source Java Projects Seminar
Cost Factors in Software Development Activities (with CQSE) Master
Automating User Acceptance Tests (with VZ) Bachelor
Change-based Test Execution Optimization in the Development Environment (with CQSE) Bachelor
The Cost of Code Reviews Seminar
Methodology to Assess File Accesses of Tests Using System Call Analysis Seminar
Smarter Testing Through Static Analysis Seminar



Semester Title Type
WS2019/20 Advanced Topics of Software Engineering (IN2309, IN2126) Lecture + Exercise
SS2020 Seminar: Software Quality Seminar
SS2020 Fortgeschrittene Themen des Softwaretests (IN2084) Lecture + Exercise
WS2020/21 Advanced Topics of Software Engineering (IN2309, IN2126) Lecture + Exercise
WS2020/21 Seminar: Software Quality Seminar
SS2021 Seminar: Software Quality Seminar
WS2021/22 Seminar: Software Quality Seminar
SS2022 Seminar: Software Quality Seminar



  • Lipp, S., Elsner, D., Kacianka, S., Pretschner, A., Böhme, M., Banescu, S. (2023). Green Fuzzing: A Saturation-based Stopping Criterion using Vulnerability Prediction. ISSTA. (accepted for publication).
  • Elsner, D., Kacianka, S., Lipp, S., Pretschner, A., Habermann, A., Graber, M., Reimer, S. (2023). BinaryRTS: Cross-language Regression Test Selection for C++ Binaries in CI. ICST. Distinguished Paper Award
  • Hundsdorfer, S.*, Elsner, D.*, Pretschner, A. (2023). DIRTS: Dependency Injection Aware Regression Test Selection. ICST.
  • Wuersching, R.*, Elsner, D.*, Leinen, F., Pretschner, A., Grueneissl, G., Neumeyr, T., Vosseler, T. (2023). Severity-Aware Prioritization of System-Level Regression Tests in Automotive Software. ICST.
  • Elsner, D., Wuersching, R., Schnappinger, M., Pretschner, A. (2022). Probe-based Syscall Tracing for Efficient and Practical File-level Test Traces. AST.
  • Elsner, D., Bertagnolli, D., Pretschner, A., Klaus, R. (2022). Challenges in Regression Test Selection for End-to-End Testing of Microservice-based Software Systems. AST.
  • Lipp, S., Elsner, D., Hutzelmann, T., Banescu, S., Pretschner, A., & Böhme, M. (2022). FuzzTastic: A Fine-grained, Fuzzer-agnostic Coverage Analyzer. ICSE-DEMO.
  • Elsner, D., Wuersching, R., Schnappinger, M., Pretschner, A., Graber, M., Dammer, R., & Reimer, S. (2022). Build System Aware Multi-language Regression Test Selection in Continuous Integration. ICSE-SEIP.
  • Haas, R.*, Elsner, D.*, Juergens, E., Pretschner, A., & Apel, S. (2021). How Can Manual Testing Processes Be Optimized? Developer Survey, Optimization Guidelines, and Case Studies. ESEC/FSE.
  • Elsner, D., Hauer, F., Pretschner, A., & Reimer, S. (2021). Empirically Evaluating Readily Available Information for Regression Test Optimization in Continuous Integration. ISSTA.
  • Maier, M.*, Elsner, D.*, Marouane, C., Zehnle, M., & Fuchs, C. (2019). DeepFlow: Detecting Optimal User Experience From Physiological Data Using Deep Neural Networks. IJCAI.
  • Elsner, D., Langer, S., Ritz, F., Müller, R., & Illium, S. (2019). Deep Neural Baselines for Computational Paralinguistics. Interspeech.
  • Maier, M., Marouane, C., & Elsner, D. (2019). DeepFlow: Detecting Optimal User Experience From Physiological Data Using Deep Neural Networks - Extended Abstract. AAMAS.
  • Elsner, D., Aleatrati Khosroshahi, P., MacCormack, A. D., & Lagerström, R. (2019). Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications. HICSS.
  • Hawlitschek, F., Kranz, T. T., Elsner, D., Fritz, F., Mense, C., Müller, M. B., & Straub, T. (2017). Sharewood-Forest–A Peer-to-Peer Sharing Economy Platform for Wild Camping Sites in Germany. Hohenheim Discussion Papers in Business, Economics and Social Sciences.