STMC: Statistical Model Checker with Stratified and Antithetic Sampling

Roohi, Nima; Wang, Yu; West, Matthew; Dullerud, Geir E.; Viswanathan, Mahesh

[Image: see text] is a statistical model checker that uses antithetic and stratified sampling techniques to reduce the number of samples and, hence, the amount of time required before making a decision. The tool is capable of statistically verifying any black-box probabilistic system that [Image: see text] can simulate, against probabilistic bounds on any property that [Image: see text] can evaluate over individual executions of the system. We have evaluated our tool on many examples and compared it with both symbolic and statistical algorithms. When the number of strata is large, our algorithms reduced the number of samples more than 3 times on average. Furthermore, being a statistical model checker makes [Image: see text] able to verify models that are well beyond the reach of current symbolic model checkers. On large systems (up to [Formula: see text] states) [Image: see text] was able to check 100% of benchmark systems, compared to existing symbolic methods in [Image: see text] , which only succeeded on 13% of systems. The tool, installation instructions, benchmarks, and scripts for running the benchmarks are all available online as open source.