Litcius/Paper detail

An efficient statistical model checker for nondeterminism and rare events

Carlos E. Budde, Pedro R. D’Argenio, Arnd Hartmanns, Sean Sedwards

2020International Journal on Software Tools for Technology Transfer39 citationsDOIOpen Access PDF

Abstract

Abstract Statistical model checking avoids the state space explosion problem in verification and naturally supports complex non-Markovian formalisms. Yet as a simulation-based approach, its runtime becomes excessive in the presence of rare events, and it cannot soundly analyse nondeterministic models. In this article, we present : a statistical model checker that combines fully automated importance splitting to estimate the probabilities of rare events with smart lightweight scheduler sampling to approximate optimal schedulers in nondeterministic models. As part of the Modest Toolset , it supports a variety of input formalisms natively and via the Jani exchange format. A modular software architecture allows its various features to be flexibly combined. We highlight its capabilities using experiments across multi-core and distributed setups on three case studies and report on an extensive performance comparison with three current statistical model checkers.

Topics & Concepts

Nondeterministic algorithmComputer scienceRotation formalisms in three dimensionsModel checkingModular designTheoretical computer scienceStatistical modelRare eventsProgramming languageParallel computingDistributed computingAlgorithmArtificial intelligenceStatisticsMathematicsGeometryFormal Methods in VerificationSoftware Reliability and Analysis ResearchSoftware Testing and Debugging Techniques