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Probabilistic Hybrid Systems Verification via SMT and Monte Carlo Techniques

01/01/2016

We apply our technique to hybrid systems involving nonlinear differential equations.

Hardware and Software: Verification and Testing, pp. 152–168, Springer International Publishing, 2016.

http://dx.doi.org/10.1007/978-3-319-49052-6_10

We develop numerically rigorous Monte Carlo approaches for computing probabilistic reachability in hybrid systems subject to random and nondeterministic parameters. Instead of standard simulation we use δδ-complete SMT procedures, which enable formal reasoning for nonlinear systems up to a user-definable numeric precision. Monte Carlo approaches for probability estimation assume that sampling is possible for the real system at hand. However, when using δδ-complete simulation one instead samples from an over approximation of the real random variable. In this paper, we introduce a Monte Carlo-SMT approach for computing probabilistic reachability confidence intervals that are both statistically and numerically rigorous. We apply our technique to hybrid systems involving nonlinear differential equations.

http://dx.doi.org/10.1007/978-3-319-49052-6_10


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