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Assume-Guarantee Abstraction Refinement for Probabilistic Systems

  • Anvesh Komuravelli
  • Corina S. Păsăreanu
  • Edmund M. Clarke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7358)

Abstract

We describe an automated technique for assume-guarantee style checking of strong simulation between a system and a specification, both expressed as non-deterministic Labeled Probabilistic Transition Systems (LPTSes). We first characterize counterexamples to strong simulation as stochastic trees and show that simpler structures are insufficient. Then, we use these trees in an abstraction refinement algorithm that computes the assumptions for assume-guarantee reasoning as conservative LPTS abstractions of some of the system components. The abstractions are automatically refined based on tree counterexamples obtained from failed simulation checks with the remaining components. We have implemented the algorithms for counterexample generation and assume-guarantee abstraction refinement and report encouraging results.

Keywords

Model Check Probabilistic System Label Transition System Automaton Learning Execution Mapping 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Anvesh Komuravelli
    • 1
  • Corina S. Păsăreanu
    • 2
  • Edmund M. Clarke
    • 1
  1. 1.Computer Science DepartmentCarnegie Mellon UniversityPittsburghUSA
  2. 2.Carnegie Mellon Silicon Valley, NASA AmesMoffett FieldUSA

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