Scholar
Andrea Stocco
Google Scholar ID: gl_lrrcAAAAJ
Technical University of Munich
Citations & Impact
Citations
2,496
H-index
27
i10-index
37
Publications
20
Co-authors
49
list available
Publications
Resume (English only)
Academic Achievements
- Published numerous papers in international conferences and journals like ASE 2025, ICSE 2025, ICST 2025a, ICST 2025b, ICSEW 2025, TOSEM 2024, EMSE 2024, TSE 2022, ASE 2022, JSEP 2021, ICST 2021, ICSE 2020, EMSE 2020, ISSREW 2020; received IEEE Computer Society TCSE Distinguished Paper Award (ICST 2025); joined program committees of several academic conferences (ISSTA 2026, SWQD 2026, FSE 2026, ASE 2025); became a member of the editorial board of the Empirical Software Engineering journal.
Research Experience
- Head of the Automated Software Testing (AST) Field of Competence at fortiss; Assistant Professor at the Technical University of Munich; involved in multiple research projects such as testing AI-based systems, grey literature analysis, studies of JS bugs, etc.
Education
- No specific education background information provided.
Background
- Scientific Researcher and head of the Automated Software Testing (AST) Field of Competence at fortiss, and an Assistant Professor at the Chair of Software Engineering for Data-intensive Applications of the School of Computation, Information and Technology of the Technical University of Munich (TUM). His research focuses on the interface between software engineering and deep learning with the goals of improving the robustness, reliability, and dependability of data-intensive software systems. Current interests involve monitoring techniques and automated functional oracles for deep learning-based systems, particularly in autonomous vehicles, and the robustness and maintainability of test suites of modern web applications.
