Annibale Panichella

Associate Professor

Delft University of Technology

Biography

I am an Associate Professor in the Software Engineering Research Group (SERG) at Delft University of Technology (TU Delft) in the Netherlands. Within SERG, I lead the Computation Intelligence for Software Engineering Lab (CISELab), where my research focuses on software testing, search-based software engineering, AI for software engineering, software testing for AI-enabled systems, and empirical software engineering.

I serve as the track lead for “Testing for and with AI” within AI4SE, TU Delft’s ICAI lab on AI for Software Engineering, funded by JetBrains. I am also involved in the FUSE Lab, a collaborative research initiative co-sponsored by Meta’s DevInfra team and TU Delft, focusing on the reliability, testing, and evolution of modern software systems. In addition, I am the principal investigator of the UBRI program at TU Delft. My research has been supported by national and international funding programs, including the European Commission’s Horizon 2020 projects on test amplification (STAMP) and testing for cyber-physical systems (COSMOS).

I have co-authored more than 130 peer-reviewed publications in leading software engineering and evolutionary computation journals and conferences. My research has contributed to advances in automated software testing, search-based software engineering, software quality assurance, and the engineering and testing of AI-enabled systems. I am grateful to have received the Most Influential Paper Awards at SANER 2024 and ICST 2025, as well as Best Paper Awards at ICPC, SBFT, and SSBSE.

I actively contribute to the software engineering research community through service in major conferences and journals. I regularly serve on program committees of leading conferences, including ICSE, ESEC/FSE, ASE, ISSTA, ICST, and GECCO, and review for journals such as IEEE Transactions on Software Engineering (TSE), ACM Transactions on Software Engineering and Methodology (TOSEM), Empirical Software Engineering (EMSE), IEEE Transactions on Evolutionary Computation (TEVC), and Software Testing, Verification and Reliability (STVR).

Interests

Computational Intelligence for Software Engineering
Test Case Generation and Fuzzing
Software Testing for AI
Validation of Generative AI
Security Testing
Regression Testing
Empirical Software Engineering
Evolutionary Computation

Education

PhD in Software Engineering, 2014

University of Salerno

Experience

Scientific Developer

Fondazione Bruno Kessler - Security & Trust

January 2014 – December 2014 Trento, Italy

Post-doc

Delft University of Technology

January 2015 – September 2016 Delft, The Netherlands

Research Associate

Interdisciplinary Centre for Security, Reliability and Trust (SnT) - University of Luxembourg

October 2016 – February 2018 Luxembourg

Research Fellow

Interdisciplinary Centre for Security, Reliability and Trust (SnT) - University of Luxembourg

February 2018 – December 2020 Luxembourg

Assistant Professor

Delft University of Technology

March 2018 – December 2022 Delft, The Netherlands

Associate Professor

Delft University of Technology

January 2023 – Present Delft, The Netherlands

Projects

AI for Fintech Research

AI for Fintech Research (AFR) is a five year collaboration between ING and Delft University of Technology. The mission of AFR is to perform world-class research at the intersection of Artificial Intelligence, Data Analytics, and Software Analytics in the context of FinTech. AFR was launched in 2020.

AI4SE Collaboration

The emergence of advanced AI-driven tools has led to a wide range of opportunities and transformations in software engineering practices and education. Recognizing this potential, JetBrains and Delft University of Technology have collaborated to establish the AI for Software Engineering Lab (AI4SE). Together, we are committed to conducting cutting-edge research on the impact and utilization of AI methodologies in software engineering. Our areas of focus include diverse facets of the domain, such as software development, testing, and programming education.

DevOps for Complex Cyber-physical Systems

Emerging Cyber-Physical Systems (CPS)—from robotics, transportation, to medical devices—play a crucial role in the quality of life of European citizens and the future of the European economy. Increasing automation to such an extent, however, gives rise to many challenges, at the crux of which lies the hardware and software symbiosis. COSMOS proposes to overcome the strain on developing and evolving high-quality, dependable CPS by employing two key technologies, namely DevOps and Artificial Intelligence (AI). These technologies offer the potential to address CPS development, verification, and evolution.

STAMP: Software Testing Amplification for DevOps

STAMP stands for Software Testing AMPlification. Leveraging advanced research in automatic test generation, STAMP aims at pushing automation in DevOps one step further through innovative methods of test amplification. STAMP will reuse existing assets (test cases, API descriptions, dependency models), in order to generate more test cases and test configurations each time the application is updated.

UBRI: University Blockchain Research Initiative

UBRI is a partnership between Ripple and top universities around the world to support academic research, technical development and innovation in blockchain, cryptocurrency and , digital payments. Ripple is providing both financial and technical resources to university partners and collaborates with faculty and students on research and technical projects.

Recent Publications

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Gregorio Dalia, Tat Luat Nguyen, Andrea Di Sorbo, Corrado Visaggio, Annibale Panichella (2026). BreachT5: Ensembling CodeT5+ Models for Multi-Label Vulnerability Detection in Smart Contracts. The 4th Workshop on Emerging Trends in Software Engineering for Blockchain (WETSEB).

Project

Alves Marinov, Paolo Arcaini, Antony Bartlett, Alessio Gambi, Fuyuki Ishikawa, Annibale Panichella (2026). Efficient Exploration of Autonomous Driving System Safety Boundaries. The IEEE Intelligent Vehicles Symposium (IV 2026).

Ali Asgari, Milan de Koning, Pouria Derakhshanfar, Annibale Panichella (2025). Metamorphic Testing of Deep Code Models: A Systematic Literature Review. ACM Transaction on Software Engineering and Methodology (TOSEM 2025).

Preprint

Antony Bartlett, Cynthia Liem, Annibale Panichella (2025). The Last Dependency Crusade: Solving Python Dependency Conflicts with LLMs. The 1st International Workshop on Agentic Software Engineering (AgenticSE).

Antony Bartlett, Cynthia Liem, Annibale Panichella (2025). The Pursuit of Diversity: Multi-Objective Testing of Deep Reinforcement Learning Agents. 17th Symposium on Search-Based Software Engineering (SSBSE 2025).

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