Model Checking as Control: Feedback Control for Statistical Model Checking of Cyber-Physical Systems

K Kalajdzic (1) , Cyrille Jegourel (2) , E Bartocci (1) , Axel Legay (2) , Scott Smolka (3) , R Grosu (1)

1 TU Wien - Vienna University of Technology = Technische Universität Wien
2 ESTASYS - Efficient STAtistical methods in SYstems of systems
3 SBU - Stony Brook University [SUNY]

We introduce feedback-control statistical system checking (FC-SSC), a new approach to statistical model checking that exploits princi-ples of feedback-control for the analysis of cyber-physical systems (CPS). FC-SSC uses stochastic system identification to learn a CPS model, im-portance sampling to estimate the CPS state, and importance splitting to control the CPS so that the probability that the CPS satisfies a given property can be efficiently inferred. We illustrate the utility of FC-SSC on two example applications, each of which is simple enough to be easily understood, yet complex enough to exhibit all of FC-SCC's features. To the best of our knowledge, FC-SSC is the first statistical system checker to efficiently estimate the probability of rare events in realistic CPS ap-plications or in any complex probabilistic program whose model is either not available, or is infeasible to derive through static-analysis techniques.

Domaines: Informatique [cs]; Sciences de l'ingénieur [physics]; Mathématiques [math]; Statistiques [stat]

K Kalajdzic, Cyrille Jegourel, E Bartocci, Axel Legay, Scott Smolka, et al.. Model Checking as Control: Feedback Control for Statistical Model Checking of Cyber-Physical Systems. 2014. ⟨hal-01087977⟩