A Theory of Probabilistic Contracts
2025 (English)In: Leveraging Applications of Formal Methods, Verification and Validation. Specification and Verification - 12th International Symposium, ISoLA 2024, Proceedings, Springer Nature , 2025, p. 296-319Conference paper, Published paper (Refereed)
Abstract [en]
In industrial-sized cyber-physical systems, ensuring fulfillment of requirements gets increasingly more costly as the number of components increases. To make the task feasible, compositional verification has been suggested as a scalable solution. Such techniques allow verification by divide-and-conquer, often using assume-guarantee contracts. Although previous research has focused mostly on the non-probabilistic setting, in the real world, probabilities often arise due to random hardware failures, stochastic communication delays, sensor ghost objects, machine learning components, rounding errors caused by finite-precision arithmetic, human behavior, and probabilistic algorithms. Therefore, for contract theories to be practically relevant to cyber-physical systems, there is a need to support probabilistic reasoning, for instance regarding safety and reliability. To this end, we propose a completely trace-based probabilistic contract theory, supporting general probability measures, continuous time, and continuous state spaces. To verify decompositions of such contracts, we also present a deductive system, which is illustrated on an industrially inspired automatic emergency braking example.
Place, publisher, year, edition, pages
Springer Nature , 2025. p. 296-319
Keywords [en]
Compositional verification, Contract theory, Probability
National Category
Computer Sciences Computer Systems
Identifiers
URN: urn:nbn:se:kth:diva-356657DOI: 10.1007/978-3-031-75380-0_17Scopus ID: 2-s2.0-85208595091OAI: oai:DiVA.org:kth-356657DiVA, id: diva2:1914827
Conference
12th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2024, Crete, Greece, October 27-31, 2024
Note
Part of ISBN 9783031753794
QC 20241121
2024-11-202024-11-202024-11-21Bibliographically approved