Publikationer pr. år
Publikationer pr. år
Andrej Kiviriga*, Kim Guldstrand Larsen, Ulrik Nyman
Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review
We introduce Randomized Reachability Analysis – an efficient and highly scalable method for detection of “rare event” states, such as errors. Due to the under-approximate nature of the method, it excels at quick falsification of models and can greatly improve the model-based development process: using lightweight randomized methods early in the development for the discovery of bugs, followed by expensive symbolic verification only at the very end. We show the scalability of our method on a number of Timed Automata and Stopwatch Automata models of varying sizes and origin. Among them, we revisit the schedulability problem from the Herschel-Planck industrial case study, where our new method finds the deadline violation three orders of magnitude faster: some cases could previously be analyzed by statistical model checking (SMC) in 23 h and can now be checked in 23 s. Moreover, a deadline violation is discovered in a number of cases that where previously intractable. We have implemented the Randomized Reachability Analysis – and made it available – in the tool Uppaal.
Originalsprog | Engelsk |
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Titel | Formal Methods for Industrial Critical Systems : 26th International Conference, FMICS 2021, Proceedings |
Redaktører | Alberto Lluch Lafuente, Anastasia Mavridou |
Antal sider | 18 |
Forlag | Springer Science+Business Media |
Publikationsdato | 2021 |
Sider | 149-166 |
ISBN (Trykt) | 9783030852474 |
DOI | |
Status | Udgivet - 2021 |
Begivenhed | 26th International Conference on Formal Methods for Industrial Critical Systems, FMICS 2021 - Virtual, Online Varighed: 24 aug. 2021 → 26 aug. 2021 |
Konference | 26th International Conference on Formal Methods for Industrial Critical Systems, FMICS 2021 |
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By | Virtual, Online |
Periode | 24/08/2021 → 26/08/2021 |
Navn | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Vol/bind | 12863 LNCS |
ISSN | 0302-9743 |
Publikation: Bidrag til tidsskrift › Konferenceartikel i tidsskrift › Forskning › peer review