An efficient statistical model checker for nondeterminism and rare events

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

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
4 Downloads (Pure)

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 modes: 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.

Original languageEnglish
Pages (from-to)759-780
Number of pages22
JournalInternational journal on software tools for technology transfer
Volume22
Issue number6
Early online date28 May 2020
DOIs
Publication statusPublished - 28 Dec 2020

Keywords

  • UT-Hybrid-D

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