EPR-based k-induction with Counterexample Guided Abstraction Refinement.

GCAI(2015)

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摘要
In recent years it was proposed to encode bounded model checking (BMC) into the effectively propositional fragment of first-order logic (EPR). The EPR fragment can provide for a succinct representation of the problem and facilitate reasoning at a higher level. In this paper we present an extension of the EPR-based bounded model checking with k-induction which can be used to prove safety properties of systems over unbounded runs. We present a novel abstraction-refinement approach based on unsatisfiable cores and models (UCM) for BMC and k-induction in the EPR setting. We have implemented UCM refinements for EPR-based BMC and k-induction in a first-order automated theorem prover iProver. We also extended iProver with the AIGER format and evaluated it over the HWMCC'14 competition benchmarks. The experimental results are encouraging. We show that a number of AIG problems can be verified until deeper bounds with the EPR-based model checking.
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关键词
counterexample guided abstraction refinement,epr-based,k-induction
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