Project Details
Verification and Analysis for Safety and Security of Applications in Life
Project Period: 1. 6. 2024 – 31. 5. 2027
Project Type: grant
Code: SEP-210979090
Agency: European Union
Program: HORIZON EUROPE
Formal methods, model-based-design, safety and security of software, economics of software tools, software engineering
VASSAL project focuses on leveraging the scientific excellence and innovation capacity of the consortium in the field of software engineering to support safety and security of digitised economies and societies. The key objective is to bring together expertise of the consortium in specific domains to enhance and create a new knowledge for robust and resilient SW engineering through scientific strategy combining model-based design, formal methods and economics for source-codes and systems.
As SW becomes more complex, ensuring its safety and security (vulnerabilities free) becomes increasingly challenging and vital, not only in safety-critical systems but across various operation systems and IoT as well.
Formal methods and model-based design are taking an increasingly significant role, building upon its already widespread use in safety-critical applications, such as automotive or aerospace. As basic building blocks in engineering process, they enable to build robust and resilient SW and HW systems (security-/safe-by-design) ensuring the reliability and correctness, leveraging cybersecurity, and improving the development life-cycle, that lead to savings in operational costs of systems.
The economic assessment and implications of advanced SW engineering tools are not commonly available. VASSAL will deliver a rare opportunity to explore and document the potential benefits of and challenges in deployment in order to leverage the awareness and make inroads to broader exploitation by end-users (especially SMEs) in segments, where these issues are being overlooked due to the alleged non-returnability of the investment.
Andriushchenko Roman, Ing. (DITS)
Bobalová Martina, Mgr., Ph.D. (ÚI)
Dacík Tomáš, Ing. (DITS)
Doskočil Radek, doc. Ing., Ph.D., MSc (ÚI)
Fiedor Jan, Ing., Ph.D. (DITS)
Hudák David, Ing. (DITS)
Jírovec Martin, Ing. (DFIT-Dean)
Karas Michal, doc. Ing., Ph.D. (ÚF)
Kozubová Hana, Mgr. (External relations)
Křena Bohuslav, Ing., Ph.D. (DITS)
Lengál Ondřej, doc. Ing., Ph.D. (DITS)
Luhan Jan, Ing., Ph.D., MSc (ÚI)
Macák Filip, Ing. (DITS)
Novotná Veronika, doc. Mgr., Ph.D. (ÚI)
Pavela Jiří, Ing. (DITS)
Reš Jakub, Ing. (DITS)
Širáňová Lenka, Ing., Ph.D. (ÚI)
Valko Roderik, MSc
Vašíček Ondřej, Ing. (DITS)
Veselá Sára, Ing.
Vojnar Tomáš, prof. Ing., Ph.D. (DITS)
Žižka Josef, Ing. (DCGM)
2025
- ANDRIUSHCHENKO, R.; ČEŠKA, M.; JUNGES, S.; MACÁK, F. Small Decision Trees for MDPs with Deductive Synthesis. In Computer Aided Verification. Springer Cham, 2025.
p. 169-192. ISBN: 978-3-031-98678-9. Detail - ANDRIUSHCHENKO, R.; ČEŠKA, M.; MACÁK, F.; FRANCESCO, P.; MICHELE, C. Decentralized Planning Using Probabilistic Hyperproperties. In Proc. of the 24th International Conference on Autonomous Agents and Multiagent Systems. Detroit: 2025.
p. 1688-1697. ISBN: 979-8-4007-1426-9. Detail - CHOCHOLATÝ, D.; HAVLENA, V.; HOLÍK, L.; HRANIČKA, J.; LENGÁL, O.; SÍČ, J. Z3-Noodler 1.3: Shepherding Decision Procedures for Strings with Model Generation. Proceedings of TACAS'25. Lecture Notes in Computer Science. Hamilton: Springer Verlag, 2025. iss. 1,
p. 23. ISSN: 0302-9743. Detail - DACÍK, T.; VOJNAR, T. RacerF: Data Race Detection with Frama-C (Competition Contribution). In Proceedings of the 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems, part 3. Lecture Notes in Computer Science. Hamilton: Springer Nature Switzerland AG, 2025.
p. 248-253. ISBN: 978-3-031-90659-6. Detail - DACÍK, T.; VOJNAR, T. RacerF: Lightweight Static Data Race Detection for C Code. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2025.
p. 37.1-37.19. ISBN: 978-3-95977-373-7. Detail - FLORIAN, S.; ROGALEWICZ, A.; VOJNAR, T.; ZULEGER, F. Compositional Shape Analysis with Shared Abduction and Biabductive Loop Acceleration. In Programming Languages and Systems - 34th European Symposium on Programming, ESOP 2025. Lecture Notes in Computer Science. Springer, 2025.
p. 230-257. ISBN: 978-3-031-91121-7. Detail - GALESLOOT, M.; ANDRIUSHCHENKO, R.; ČEŠKA, M.; JUNGES, S.; JANSEN, N. Robust Finite-Memory Policy Gradients for Hidden-Model POMDPs. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2025.
p. 8518-8526. ISBN: 978-1-956792-06-5. Detail