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Deep Random Search for Efficient Model Checking of Timed Automata

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Composition of Embedded Systems. Scientific and Industrial Issues (Monterey Workshop 2006)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4888))

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Abstract

We present DRS (Deep Random Search), a new Las Vegas algorithm for model checking safety properties of timed automata. DRS explores the state space of the simulation graph of a timed automaton by performing random walks up to a prescribed depth. Nodes along these walks are then used to construct a random fringe, which is the starting point of additional deep random walks. The DRS algorithm is complete, and optimal to within a specified depth increment. Experimental results show that it is able to find extremely deep counter-examples for a number of benchmarks, outperforming Open-Kronos and Uppaal in the process.

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Fabrice Kordon Oleg Sokolsky

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Grosu, R., Huang, X., Smolka, S.A., Tan, W., Tripakis, S. (2008). Deep Random Search for Efficient Model Checking of Timed Automata. In: Kordon, F., Sokolsky, O. (eds) Composition of Embedded Systems. Scientific and Industrial Issues. Monterey Workshop 2006. Lecture Notes in Computer Science, vol 4888. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77419-8_7

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  • DOI: https://doi.org/10.1007/978-3-540-77419-8_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77418-1

  • Online ISBN: 978-3-540-77419-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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