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 tool paper, we present modes: a statistical model checker that combines fully automated importance splitting to efficiently 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 with an experimental evaluation across multi-core and distributed setups on three exemplary case studies.
|Title of host publication||Proceedings of the 24th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2018)|
|Editors||Dirk Beyer, Marieke Huisman|
|Place of Publication||Cham|
|Number of pages||19|
|Publication status||Published - 2018|
|Name||Lecture Notes in Computer Science|