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Better Automated Importance Splitting for Transient Rare Events

  • Carlos E. Budde
  • Pedro R. D’Argenio
  • Arnd Hartmanns
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10606)

Abstract

Statistical model checking uses simulation to overcome the state space explosion problem in formal verification. Yet its runtime explodes when faced with rare events, unless a rare event simulation method like importance splitting is used. The effectiveness of importance splitting hinges on nontrivial model-specific inputs: an importance function with matching splitting thresholds. This prevents its use by non-experts for general classes of models. In this paper, we propose new method combinations with the goal of fully automating the selection of all parameters for importance splitting. We focus on transient (reachability) properties, which particularly challenged previous techniques, and present an exhaustive practical evaluation of the new approaches on case studies from the literature. We find that using Restart simulations with a compositionally constructed importance function and thresholds determined via a new expected success method most reliably succeeds and performs very well. Our implementation within the Modest Toolset supports various classes of formal stochastic models and is publicly available.

Notes

Acknowledgements

We are grateful to José Villén-Altamirano for very helpful discussions that led to our eventual design of the expected success method.

This work is supported by the 3TU.BSR project, ERC grant 695614 (POWVER), the NWO SEQUOIA project, and SeCyT-UNC projects 05/BP12 and 05/B497.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Carlos E. Budde
    • 1
    • 2
  • Pedro R. D’Argenio
    • 2
    • 3
  • Arnd Hartmanns
    • 1
  1. 1.University of TwenteEnschedeThe Netherlands
  2. 2.Universidad Nacional de CórdobaCórdobaArgentina
  3. 3.Saarland UniversitySaarbrückenGermany

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