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Automated Assume-Guarantee Reasoning by Abstraction Refinement

  • Mihaela Gheorghiu Bobaru
  • Corina S. Păsăreanu
  • Dimitra Giannakopoulou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5123)

Abstract

Current automated approaches for compositional model checking in the assume-guarantee style are based on learning of assumptions as deterministic automata. We propose an alternative approach based on abstraction refinement. Our new method computes the assumptions for the assume-guarantee rules as conservative and not necessarily deterministic abstractions of some of the components, and refines those abstractions using counterexamples obtained from model checking them together with the other components. Our approach also exploits the alphabets of the interfaces between components and performs iterative refinement of those alphabets as well as of the abstractions. We show experimentally that our preliminary implementation of the proposed alternative achieves similar or better performance than a previous learning-based implementation.

Keywords

Model Check Label Transition System Concrete State Membership Query State Model Checker 
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 2008

Authors and Affiliations

  • Mihaela Gheorghiu Bobaru
    • 1
    • 2
  • Corina S. Păsăreanu
    • 1
  • Dimitra Giannakopoulou
    • 1
  1. 1.PSGS and RIACS, NASA Ames Research CenterMoffett FieldUSA
  2. 2.Department of Computer ScienceUniversity of TorontoTorontoCanada

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