To combat the state-space explosion problem and ease system development, we present a new refinement checking (falsification) method for Timed I/O Automata based on random walks. Our memoryless heuristics Random Enabled Transition (RET) and Random Channel First (RCF) provide efficient and highly scalable methods for counterexample detection. Both RET and RCF operate on concrete states and are relieved from expensive computations of symbolic abstractions. We compare the most promising variants of RET and RCF heuristics to existing symbolic refinement verification of the Ecdar tool. The results show that as the size of the system increases our heuristics are significantly less prone to exponential increase of time required by Ecdar to detect violations: in very large systems both "wide" and "narrow" violations are found up to 600 times faster and for extremely large systems when Ecdar timeouts, our heuristics are successful in finding violations.
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 modelbased 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 hours and can now be checked in 23 seconds. 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.
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 modelbased 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 hours and can now be checked in 23 seconds. 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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.