Test-Input Generation Professors and Supervisors in Germany

Antonio Filieriمشاهده پروفایل

دانشیار مهمان

Max Planck Institute for Security and PrivacyGermany

Antonio Filieri is a Senior Applied Scientist at Amazon Web Services (AWS) and holds a Visiting Associate Professor position at the Department of Computing, Imperial College London. Previously, he was a tenured Associate Professor at Imperial College London (2022-2024) and Assistant Professor (2016-2022), and served as Assistant Professor at the University of Stuttgart between 2013 and 2015. His academic career spans over a decade with significant contributions to software engineering research. Dr. Filieri's research focuses on formal mathematical methods for software design, verification, self-adaptation, and security. His primary research areas include static analysis, privacy, and automated test generation for security; exact and approximate methods for probabilistic program analysis; control theory for adaptive software; quantitative verification and model checking; and runtime-efficient and incremental verification. His work bridges theoretical foundations with practical applications in industry settings, particularly in cloud computing and security domains. His recent publications demonstrate a strong focus on probabilistic methods for software analysis, security testing, and performance modeling. The research trends show increasing integration of formal methods with machine learning techniques, particularly in test oracle generation and neural network analysis. There's also a clear emphasis on scalability and practical applicability of verification techniques to real-world systems like serverless computing and microservices architectures. Dr. Filieri has received numerous prestigious awards for his contributions: Best Student Paper Award (2025) for 'Robust Probabilistic Model Checking with Continuous Reward Domains' ACM Distinguished Paper Award (2023) for 'Sibyl: Improving Software Engineering Tools with SMT Selection' Best Paper Award (2022) for 'Enhancing Performance Modeling of Serverless Functions via Static Analysis' Best Artifact Award (2017) for 'Self-adaptive video encoder: comparison of multiple adaptation strategies made simple' Most Influential Paper Award (awarded at SEAMS 2025) for 'Software Engineering Meets Control Theory' ACM SigSoft Distinguished Paper Award (2011) for 'Run-time Efficient Probabilistic Model Checking' Dr. Filieri has advised several PhD students including Donato Clun (2024), Runan Wang (2024), and Xiaotong Ji (expected 2025). His advising focuses on probabilistic program analysis, automated testing, and security verification. His research has been supported by significant grants from both academic and industry sources, enabling collaborations across multiple institutions and contributing to advancements in software engineering practices. While specific lab information isn't prominently featured in the provided materials, Dr. Filieri's work suggests strong connections with research groups focused on formal methods, software verification, and adaptive systems at both Imperial College London and AWS. His research often involves interdisciplinary collaboration between theoretical computer science and practical software engineering challenges.

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Arda Goknilمشاهده پروفایل

پژوهشگر

Max Planck Institute for Security and PrivacyGermany

Arda Goknil is a researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg, actively contributing to software engineering research with a focus on security testing and model-driven methodologies. His work bridges theoretical foundations with practical tool development for critical software verification challenges. His research centers on software security testing, metamorphic testing frameworks, model-driven engineering, and formal methods. Key contributions include developing specialized tools for web application security analysis and automated model reasoning, addressing vulnerabilities through innovative testing approaches that transform security requirements into executable validation procedures. Analysis of his 2018-2020 publications reveals a consistent emphasis on metamorphic relations for security testing in web environments and formal logic integration for model verification. His work demonstrates strong interdisciplinary connections between cybersecurity, automated testing, and model transformation, with practical applications in vulnerability detection and security policy enforcement. As part of SnT - Luxembourg's premier research center for digital trust - he collaborates within multidisciplinary teams advancing security, reliability, and trustworthiness in modern software systems through rigorous academic research and tool-oriented solutions.

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Jingyue Liمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Jingyue Li is a Professor in the Department of Computer Science at the Norwegian University of Science and Technology (NTNU), within the Faculty of Information Technology and Electrical Engineering. She earned her Ph.D. in Software Engineering from NTNU in 2006 and has extensive industrial experience including positions at IBM and DNV Research and Innovation. Her educational background includes: Ph.D. in Software Engineering from NTNU (2006) Professor Li's research spans several key areas in software engineering with a focus on both theoretical and practical applications. Her work bridges traditional software engineering practices with emerging technologies, particularly in the domain of security and blockchain systems. She has conducted extensive empirical research and applied design science methodologies to develop innovative tools and approaches. Her recent publications demonstrate a strong trend toward blockchain technologies, software security, and the intersection of AI with software engineering. The research shows increasing focus on practical applications of blockchain in decentralized autonomous organizations, consensus protocols, and security vulnerabilities in smart contracts. There's also significant work on integrating security practices into DevOps (DevSecOps) and applying machine learning techniques to software engineering problems. Professor Li has received recognition through her leadership roles in major conferences: General Chair for FSE 2025 (The ACM International Conference on Foundations of Software Engineering) Member of the EASE (International Conference on Evaluation and Assessment in Software Engineering) steering committee In terms of research leadership, Professor Li has served as Principal Investigator (PI) or Key Scientist on numerous research projects including TRACE4EU (2023-2025), PaaSforChain (2020-2023), CyberSmart (2017-2020), and several others focused on blockchain, security, and software engineering. She has also conducted research visits to institutions including University College London, University of Washington, Hiroshima University, and Peking University. Her research group appears to be actively engaged in both theoretical and applied research, with strong industry connections through projects like CyberSmart and SecureCyber that address real-world challenges in cybersecurity and smart city infrastructure.

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Ali Mesbahمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Ali Mesbah is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia (UBC), where he leads the SALT lab. His research focuses on software engineering with emphasis on AI-driven software analysis, software testing, and software evolution. Previously, he was a Visiting Research Scientist at Google during 2017-2018. Dr. Mesbah received his BSc/MSc (2003) and PhD (2009) degree cum laude in Computer Science from the Delft University of Technology (TUDelft). After completing a postdoctoral fellowship with the Software Engineering Research Group at TUDelft and a Visiting Researcher position at Fujitsu Laboratories of America, he joined UBC in 2011. His research interests span software engineering with particular focus on AI-driven software analysis, software testing, software evolution, program comprehension, fault localization and repair. His work has significant applications in web application testing, JavaScript analysis, and automated program repair. He has pioneered techniques for testing modern web applications, analyzing JavaScript code, and leveraging AI for software maintenance tasks. His recent publications demonstrate a clear evolution toward integrating large language models with traditional program analysis techniques, focusing on test generation, bug repair, and understanding multi-hunk patches. His work bridges theoretical software engineering concepts with practical applications, particularly in web technologies and AI-assisted development. Amazon Research Award (2023) Killam Accelerator Research Fellowship (KARF) (2020) Killam Faculty Research Prize (2019) NSERC Discovery Accelerator (DAS) award (2016) ACM Distinguished Paper Awards at ICSE (2009, 2014) IEEE Distinguished Paper Award at ICST (2018) Best Paper Award at ESEM (2015) Best Paper Award at ICWE (2013) Dr. Mesbah has advised numerous PhD and MASc students, many of whom have gone on to positions at leading technology companies including Google, Amazon, Apple, Microsoft, and SAP. His research has been supported by various grants including the Amazon Research Award and NSERC funding. He leads the SALT lab at UBC, which focuses on software analysis, testing, and learning, with current research directions including AI-driven software engineering, web application testing, and program repair. The lab maintains active collaborations with industry partners and academic institutions worldwide.

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Shing-Chi Cheungمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Shing-Chi Cheung is a Professor of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), School of Engineering. He founded the CASTLE research group and co-founded the International Workshop on Automation of Software Testing (AST) in 2006. His leadership includes serving as General Chair of FSE 2014 and chairing multiple APSEC conferences. His research focuses on software quality enhancement through program analysis, testing, debugging, and AI techniques, targeting Android apps, open-source software, deep learning systems, smart contracts, and spreadsheets. Current projects include metamorphic testing frameworks, binary analysis tools, and vulnerability detection systems for emerging technologies. His publication portfolio demonstrates consistent contributions to software engineering since 2016, with recent work emphasizing AI-integrated testing methodologies, smart contract security, and deep learning system reliability. Key trends show increasing focus on cross-language analysis, data visualization quality, and compiler-level verification for modern software stacks. Distinguished Member of the ACM Fellow of the British Computer Society Editorial board member: Science of Computer Programming (SCP), Journal of Computer Science and Technology (JCST) Former editorial board member: IEEE Transactions on Software Engineering (2006-2009), Information and Software Technology (2012-2015) Four patents in China and the United States Cheung actively mentors through the CASTLE research group and serves on program committees for major conferences including ICSE, ESEC/FSE, and ISSTA. His work bridges academic research with practical applications through industry collaborations and tool development. He has contributed to numerous workshops and symposia as steering committee member and program chair.

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Chang-ai Sunمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Chang-ai Sun is a full professor at the School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB). He currently serves as Vice Dean of the Institute for Multidisciplinary Innovation (IMI), Head of the Department of Computer Science, and Director of the Software Engineering Institute at USTB. He received his bachelor's degree in computer science from the University of Science and Technology Beijing and his PhD in computer science from Beihang University, China. Prof. Sun's primary research focuses on software engineering with particular emphasis on software testing, program analysis, and service-oriented computing. Recently, he has been devoted to developing novel theories, techniques, and supporting tools for intelligent software development and maintenance. His work spans theoretical foundations to practical applications in software quality assurance, with increasing focus on AI-driven approaches to traditional software engineering challenges. His publication record shows consistent contributions to metamorphic testing, program repair, and the application of AI techniques to software engineering problems. Recent work explores the intersection of large language models and software testing methodologies, demonstrating both theoretical innovation and practical implementation. Prof. Sun has received significant recognition for his contributions: 11 national Software Prototype/Service Innovation Awards Senior Member of IEEE Distinguished Member of China Computer Federation (CCF) As principal investigator and major investigator, he has completed over 40 research projects funded by the European Union, Australia, China, and Hong Kong. His extensive grant portfolio demonstrates strong international collaboration and significant impact in the software engineering community. He actively mentors students and junior researchers through his leadership roles. Prof. Sun leads the Software Engineering Institute at USTB, where his team focuses on advancing research in software testing, program analysis, and intelligent software development tools. His leadership extends to departmental administration as Head of the Department of Computer Science, shaping curriculum and research directions for one of China's leading technical universities.

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Minxue Panمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Minxue Pan is a Professor and PhD supervisor at the Software Institute, State Key Laboratory for Novel Software Technology, Nanjing University, China. His research focuses on the dependability of complex software systems, with expertise spanning software modeling and verification, software analysis and testing, cyber-physical systems, mobile computing, and intelligent software engineering. Ph.D. in Computer Science and Technology from Nanjing University (2014), supervised by Prof. Xuandong Li B.Sc. from Nanjing University Studied at UC Berkeley's Department of Electrical Engineering and Computer Sciences (2009-2010) under Prof. Edward A. Lee Professor Pan's research interests center on improving software dependability through innovative approaches to modeling, analysis, and testing. His work spans traditional software systems, mobile applications (particularly Android), cyber-physical systems, and the application of AI techniques to software engineering problems. He has made significant contributions to GUI testing, vulnerability detection, and deep learning applications in software engineering. His recent publications (2024-2025) demonstrate a strong focus on applying advanced machine learning techniques to software testing and security challenges. Key trends include leveraging large language models for test migration, enhancing fault localization with graph learning and contrastive learning, developing specialized frameworks for Android security analysis, and improving test efficacy through GUI and functional equivalence. His work consistently targets real-world industrial settings and addresses practical challenges in mobile and complex software systems. ISSTA 2020 Distinguished Paper Award ICSE 2025 Best Artifact Award Professor Pan actively advises graduate students and has developed several notable tools including Q-testing (reinforcement-learning based Android testing), ISDChecker (model checking for interrupt-driven systems), PREFEST (preference-wise testing for Android), Sketchoid (GUI code search), and PI-REC (hand-drawn draft conversion). His research is supported by extensive publication records in top-tier software engineering venues including ASE, ICSE, FSE, ISSTA, and TOSEM. He teaches undergraduate courses in Advanced Programming with C++, Software System Design, and Software Construction, as well as graduate courses in Advanced Software Design. His laboratory work focuses on developing practical solutions for real-world software dependability challenges through the State Key Laboratory for Novel Software Technology.

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Antonio Ruiz-Cortésمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Antonio Ruiz-Cortés is Professor of Software and Service Engineering at the University of Seville and an elected member of the Academy of Europe. He currently heads the Applied Software Engineering Group at the University of Seville and has served as President of the Spanish Society on Software Engineering (SISTEDES) since September 2018. His research spans multiple critical areas of modern software engineering: Service-Oriented Computing Software Architecture Business Process Management Testing methodologies Software Product Lines Automatic Model Analysis Professor Ruiz-Cortés has established himself as a leading researcher in REST API testing and verification, with multiple influential publications in top software engineering conferences. His work bridges traditional software engineering with emerging domains like quantum computing, demonstrating remarkable adaptability. He has developed practical tools including RESTest and AGORA that address real-world testing challenges faced by industry practitioners. His scientific contributions have been recognized with the Most Influential Paper award at SPLC 2017. He serves as associate editor for Springer Computing and has organized major conferences including JCIS 2008, SPLC 2017, SISTEDES 2018 and BPM 2020, demonstrating significant leadership in the academic community. Professor Ruiz-Cortés maintains active research funding supporting his work in service-oriented computing and software testing, though specific grant details aren't provided in the available information. His presidency of SISTEDES reflects his commitment to advancing software engineering research in Spain.

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Gary Tanمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Gang (Gary) Tan is a Professor in the Computer Science and Engineering Department at Pennsylvania State University, co-directing the Institute for Networking and Security Research (INSR). His research bridges computer security, formal methods, and programming languages to develop practical solutions for software vulnerabilities and AI fairness. Education: B.E. in Computer Science from Tsinghua University Ph.D. in Computer Science from Princeton University Dr. Tan specializes in applying compiler techniques and formal verification to security challenges, with seminal work on cache side-channel attacks and fairness in machine learning. His Security of Software (SOS) Group develops frameworks that integrate theoretical guarantees into real-world systems, emphasizing measurable security outcomes and ethical AI. Recent projects focus on quantifying bias in neural networks and mitigating speculative execution vulnerabilities. Analysis of his 2021-2025 publications reveals a strategic pivot toward AI security, where he pioneers methods for fairness testing (e.g., information-theoretic debugging) and repair (e.g., NeuFair). Concurrently, his security work evolves from foundational side-channel research (SpecSafe, 2021) toward hardware-software co-design solutions, demonstrating consistent innovation across theoretical and applied domains. Scientific Awards: James F. Will Career Development Professorship NSF CAREER Award Google Research Award (two instances) Distinguished Reviewer Award at 2018 IEEE Symposium on Security and Privacy Outstanding Research Award at Penn State Ruth and Joel Spira Excellence in Teaching Award Best Paper Award at PLDI 2024 Dr. Tan leads the SOS Group with funding from NSF (including CAREER), DARPA (ISAT study group membership), and industry partners like Google. His grants support interdisciplinary projects spanning secure compilation, fairness engineering, and hardware security, while his teaching excellence award reflects commitment to pedagogy in core systems courses. He co-directs Penn State's Institute for Networking and Security Research (INSR), fostering collaboration between systems, security, and AI researchers. The SOS Group maintains active partnerships with industry security teams and contributes to open-source tools for vulnerability detection, with recent work expanding into fairness certification for machine learning pipelines.

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Lars Grunskeمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Lars Grunske is a Professor in the Department of Computer Science at Humboldt University of Berlin, Germany. His academic career spans multiple institutions across Germany, Australia, and internationally, with a strong focus on research and conference participation in software engineering. His educational background includes a PhD in computer science from the University of Potsdam (Hasso-Plattner-Institute for Software Systems Engineering) in 2004. Professor Grunske's research interests center on modeling and verification of systems and software, with particular emphasis on automated analysis techniques. His work primarily focuses on probabilistic and timed model checking and model-based dependability evaluation of complex software intensive systems. He has made significant contributions to software testing, program repair, formal methods, and the application of machine learning techniques to software engineering problems. His publication record shows consistent contributions to top software engineering conferences over the past decade, with recent work exploring the intersection of AI/ML with traditional software engineering challenges. His research demonstrates an evolution from foundational model checking techniques toward more practical applications in software testing and repair. Boeing Postdoctoral Research Fellow Professor Grunske actively mentors through conference activities including chairing mentoring circles at ICSE 2021. He serves on numerous program committees for major software engineering conferences including ASE, ICSE, ESEC/FSE, and others, demonstrating his standing in the academic community. His involvement spans multiple roles from committee member to track chair and award committee positions. He maintains an active research laboratory focused on software verification and testing, as indicated by his departmental affiliation and research website.

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Andreas Zellerمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Andreas Zeller serves as Professor for Software Engineering at Saarland University and faculty at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. His dual appointments position him at the intersection of academic research and practical cybersecurity applications, contributing significantly to both institutions' research profiles. Professor Zeller's research spans multiple dimensions of software quality assurance, with particular expertise in automated debugging techniques, mining software repositories for insights, specification mining, and security testing methodologies. His work consistently bridges theoretical foundations with practical implementation, resulting in tools and frameworks adopted widely in both research and industry contexts. Analysis of his recent publications reveals an evolutionary trajectory from foundational debugging work toward increasingly sophisticated grammar-based testing approaches, with notable integration of machine learning techniques in recent years. His research demonstrates consistent focus on improving software reliability through automated analysis, with growing emphasis on security applications including XML injection testing, GNSS module security, and binary file format vulnerabilities. Recipient of two ERC Advanced Grants (including the S3 project) ACM Fellow ACM SIGSOFT Outstanding Research Award Professor Zeller has successfully secured substantial research funding through competitive mechanisms including ERC grants, enabling his team to pursue ambitious research agendas. His leadership extends to mentoring through his roles as doctoral symposium co-chair and active participation in new faculty development initiatives. He maintains strong engagement with the research community through numerous program committee memberships and conference organization roles. At CISPA Helmholtz Center for Information Security, Zeller contributes to the center's mission through research focused on software security testing and analysis. His work on grammar-based testing and fuzzing directly addresses critical security challenges in modern software systems, with practical applications for improving software resilience against attacks.

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Ajitha Rajanمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Ajitha Rajan is a Professor (Personal Chair of Software Testing & Verification) at the School of Informatics, University of Edinburgh. She joined the university in December 2012 as a Reader (equivalent to Associate Professor in American terms) and was promoted to Professor in 2024. Prior to her position at Edinburgh, she held postdoctoral positions at Oxford University and Laboratoire d'Informatique de Grenoble in France. She earned her PhD in Computer Science from the University of Minnesota in August 2009 under Professor Mats Heimdahl. Her research focuses on two primary directions: Automated Software Testing (including test input generation, test oracles, and coverage measurement) and Biomedical AI (particularly cancer survival models and interpretability for biological sequences and medical images). Her work has applications in safety-critical systems, blockchains, embedded systems, and medical diagnostics. She has made significant contributions to explainable AI for healthcare applications, especially in lung cancer detection and cancer survival analysis. Her recent publications demonstrate a strong trend toward interdisciplinary research at the intersection of software engineering and biomedical applications. She has numerous publications in top venues including ICSE, ASE, and healthcare-focused conferences. Her work increasingly focuses on making AI systems more interpretable and trustworthy, particularly in medical contexts where model decisions can have life-or-death consequences. ACM SIGSOFT Distinguished Reviewer Award, ISSTA 2025 Best Paper Award at ICHI 2025 Promoted to Professor (Chair in Software Testing & Verification) 2024 SICSA Best Supervisor Award 2024 ACM Distinguished Paper Award 2008 Professor Rajan actively supervises PhD students in both software testing and biomedical AI domains. She leads several funded projects including MANIFEST (a cancer immunotherapy response research platform), a Huawei Joint Lab project on RobustCheck, a Royal Society Industry Fellowship on AutoTest, and the KATY project on clinical knowledge for personalized medicine. Her research group includes current PhD students working on explainable AI for medical image analysis, scenario-based testing for autonomous driving, and protein design applications.

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Zhenbang Chenمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Zhenbang Chen is a Professor in the College of Computer at National University of Defense Technology (NUDT), China. His academic career spans over a decade with significant contributions to software engineering, particularly in program analysis and formal methods. He has served on program committees for major conferences including ASE, ICSE, and FSE, and has been actively involved in research that bridges theoretical formal methods with practical software engineering applications. Dr. Chen received his Ph.D. and Bachelor degrees in computer science from National University of Defense Technology (NUDT) in June 2009 and July 2002, respectively. His educational background from NUDT has provided a strong foundation for his research in software engineering and formal methods. Ph.D. in Computer Science, National University of Defense Technology (NUDT), 2009 Bachelor's Degree in Computer Science, National University of Defense Technology (NUDT), 2002 Zhenbang Chen's research primarily focuses on program analysis, with special emphasis on symbolic execution techniques. His work extends to formal methods and their practical applications in software engineering. He investigates constraint solving approaches to improve the efficiency of program analysis and explores program synthesis techniques to automate software development tasks. His research bridges theoretical foundations with practical software engineering challenges, particularly in the areas of software verification and testing. His recent work has increasingly focused on optimizing symbolic execution through novel constraint solving techniques and exploring multi-modal approaches to behavior tree synthesis. This demonstrates his commitment to advancing both the theoretical underpinnings and practical applications of software analysis techniques. Professor Chen's publication record shows a consistent focus on symbolic execution and constraint solving, with a clear progression toward more sophisticated optimization techniques. His recent work demonstrates a shift toward multi-objective optimization for floating-point constraints and multi-modal approaches to program synthesis. The research spans both theoretical foundations and practical implementations, with several tools developed from his research participating in international competitions. Dr. Chen's research excellence has been recognized through multiple prestigious awards: ACM SIGSOFT Distinguished Paper Award for FSE 2025 paper "QSF: Multi-Objective Optimization based Efficient Solving for Floating-Point Constraints" ACM SIGSOFT Distinguished Paper Award for ISSTA 2021 paper "Type and interval aware array constraint solving for symbolic execution" ACM SIGSOFT Distinguished Paper Award for ICSE 2018 paper "Towards optimal concolic testing" Bronze Medal (3rd place) in Cover-Branches category at Test-COMP 2025 for the FDSE tool Professor Chen is actively involved in mentoring the next generation of researchers, currently seeking Ph.D. and M.Sc. students to work with him on cutting-edge research in program analysis and formal methods. His research group has developed several tools that have gained recognition in international competitions, including AISE which ranked 1st in SV-COMP 2025's ReachSafety-Loops category and FDSE which won Bronze Medal in Test-COMP 2025. His research has been supported by grants that enable participation in major international conferences and competitions, fostering collaborations with researchers worldwide. Dr. Chen leads a research group focused on program analysis and formal methods at NUDT. His team has developed several notable tools including AISE for program verification and FDSE for software testing, which have achieved top rankings in international competitions like SV-COMP and Test-COMP. The research group maintains active collaborations with other institutions and participates regularly in major software engineering conferences, contributing to both theoretical advancements and practical tool development in the field.

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Andrea Arcuriمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Andrea Arcuri is a Professor of Software Engineering at Kristiania University College in Oslo, Norway, where he leads the AISE lab. Since 2020, he also holds a part-time position as Adjunct Professor at Oslo Metropolitan University. After 5 years in industry (WesternGeco and Scienta/Telenor), he returned to academia full-time in October 2016. His research primarily focuses on automated software testing and search-based software engineering. Prof. Arcuri's research interests center around Software Testing , Search-Based Software Engineering , and Automated Testing techniques. He has made significant contributions to the field through the development of testing tools like EvoMaster for system-level test generation and EvoSuite for unit test generation. His work bridges theoretical foundations with practical applications, particularly in RESTful API testing and enterprise systems. His recent publications show a strong trend toward practical applications of search-based testing in industry settings, with particular emphasis on RESTful API testing, fuzz testing, and integration with modern development practices like DevOps. The research spans both theoretical foundations of search-based testing and practical tool development. ACM SIGSOFT Impact Paper Award 2023 for EvoSuite ICST 2022 10-Year Most Influential Paper Award ICSE 2021 10-Year Most Influential Paper Award Ranked 2nd Most Active Early Stage SE Researcher in JSS'18 Multiple Best/Distinguished Paper awards at SSBSE, ASE, and ISSTA Prof. Arcuri actively supervises PhD students and post-docs, including Iva Kertusha, Susruthan Seran, and Onur Duman. He serves in leadership roles for major conferences, including as FSE 2025 Artifact Track Chair and ICST 2022 Test Tool and Demo Track Chair. His research is supported through various academic grants and industry collaborations. He leads the AISE (Artificial Intelligence and Software Engineering) lab at Kristiania University College, where his team develops and maintains the EvoMaster system test generation tool. The lab focuses on practical applications of search-based software testing in real-world enterprise settings.

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