Our society and economy rely on the well-operation of highly dynamic and complex safety-critical systems. Users need to be able to place a high level of trust in the operation of such systems. However, uncertainty in the environment, security issues, as well as errors in physical devices pose a serious threat to their reliable operation.

To increase reliability, formal methods aim at providing modeling approaches and corresponding analysis techniques to examine how such systems behave. Stochastic hybrid models are well-suited to naturally model a wide range of relevant real-world systems, where discrete and continuous behavior as well as random aspects need to be considered in combination. However, the expressivity of such models turns their analysis to a highly challenging task, for which currently only a few methods and tools are available. Such methods make use of abstraction and approximation and the accuracy of the computed results decreases significantly with the size of the model at hand.

In this seminar we discuss novel algorithmic approaches for the reachability analysis of stochastic hybrid models.

Creative Commons BY 3.0 DE

Erika Abraham