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Exploiting resolution proofs to speed up LTL vacuity detection for BMC

  • Jocelyn SimmondsEmail author
  • Jessica Davies
  • Arie Gurfinkel
  • Marsha Chechik
Regular Paper

Abstract

When model-checking reports that a property holds on a model, vacuity detection increases user confidence in this result by checking that the property is satisfied in the intended way. While vacuity detection is effective, it is a relatively expensive technique requiring many additional model-checking runs. We address the problem of efficient vacuity detection for Bounded Model Checking (BMC) of linear temporal logic properties, presenting three partial vacuity detection methods based on the efficient analysis of the resolution proof produced by a successful BMC run. In particular, we define a characteristic of resolution proofs— peripherality—and prove that if a variable is a source of vacuity, then there exists a resolution proof in which this variable is peripheral. Our vacuity detection tool, VaqTree, uses these methods to detect vacuous variables, decreasing the total number of model-checking runs required to detect all sources of vacuity.

Keywords

Vacuity detection Robustness Linear temporal logic Bounded model checking 

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Jocelyn Simmonds
    • 1
    Email author
  • Jessica Davies
    • 1
  • Arie Gurfinkel
    • 2
  • Marsha Chechik
    • 1
  1. 1.Department of Computer ScienceUniversity of TorontoTorontoCanada
  2. 2.Software Engineering InstituteCarnegie Mellon UniversityPittsburghUSA

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