Interpolation-sequence based model checking

Vizel, Yakir; Grumberg, Orna

doi:10.1109/fmcad.2009.5351148

Cited by 45 publications

(34 citation statements)

References 15 publications

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“…Secondly, we show that our SAT Modulo SAT solver produces sequence interpolants [5], [21], by extending previous work by Chockler et al [6]. These sequence interpolants are produced without requiring explicit proof-traces.…”

Section: Introductionmentioning

confidence: 80%

Efficient modular SAT solving for IC3

Bayless

Val

Ball

et al. 2013

2013 Formal Methods in Computer-Aided Design

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Abstract-We describe an efficient way to compose SAT solvers into chains, while still allowing unit propagation between those solvers. We show how such a "SAT Modulo SAT" solver naturally produces sequence interpolants as a side effect -there is no need to generate a resolution proof and post-process it to extract an interpolant. We have implemented a version of IC3 using this SAT Modulo SAT solver, which solves both more SAT instances and more UNSAT instances than PDR and IC3 on each of the 2008, 2010, and 2012 Hardware Model Checking Competition benchmarks.

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Section: Introductionmentioning

confidence: 80%

Efficient modular SAT solving for IC3

Bayless

Val

Ball

et al. 2013

2013 Formal Methods in Computer-Aided Design

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“…Several verification approaches such as [3], [10], [14] depend on the path interpolation property (PI). In [13] the authors show that LISs can be employed to generate path interpolants by providing a sequence of labeling functions that are decreasing in terms of strength.…”

Section: B Path Interpolation Propertymentioning

confidence: 99%

On interpolants and variable assignments

Jančík¹,

Kofroň²,

Rollini³

et al. 2014

2014 Formal Methods in Computer-Aided Design (FMCAD)

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Abstract-Craig interpolants are widely used in program verification as a means of abstraction. In this paper, we (i) introduce Partial Variable Assignment Interpolants (PVAIs) as a generalization of Craig interpolants. A variable assignment focuses computed interpolants by restricting the set of clauses taken into account during interpolation. PVAIs can be for example employed in the context of DAG interpolation, in order to prevent unwanted out-of-scope variables to appear in interpolants. Furthermore, we (ii) present a way to compute PVAIs for propositional logic based on an extension of the Labeled Interpolation Systems, and (iii) analyze the strength of computed interpolants and prove the conditions under which they have the path interpolation property.

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“…ITP uses interpolants to over-approximate image computations. Since [14], interpolants have been applied in several model checking algorithms [11,12,15,20,21].…”

Section: Introductionmentioning

confidence: 99%

Efficient Generation of Small Interpolants in CNF

Vizel

Ryvchin

Nadel

2013

Computer Aided Verification

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Abstract. Interpolation-based model checking (ITP) [14] is an efficient and complete model checking procedure. However, for large problems, interpolants generated by ITP might become extremely large, rendering the procedure slow or even intractable. In this work we present a novel technique for interpolant generation in the context of model checking. The main novelty of our work is that we generate small interpolants in Conjunctive Normal Form (CNF) using a twofold procedure: First we propose an algorithm that exploits resolution refutation properties to compute an interpolant approximation. Then we introduce an algorithm that takes advantage of inductive reasoning to turn the interpolant approximation into an interpolant. Unlike ITP, our approach maintains only the relevant subset of the resolution refutation. In addition, the second part of the procedure exploits the properties of the model checking problem at hand, in contrast to the general-purpose algorithm used in ITP. We developed a new interpolation-based model checking algorithm, called CNF-ITP. Our algorithm takes advantage of the smaller interpolants and exploits the fact that the interpolants are given in CNF. We integrated our method into a SAT-based model checker and experimented with a representative subset of the HWMCC'12 benchmark set. Our experiments show that, overall, the interpolants generated by our method are 42 times smaller than those generated by ITP. Our CNF-ITP algorithm outperforms ITP, and at times solves problems that ITP cannot solve. We also compared CNF-ITP to the successful IC3 [3] algorithm. We found that CNF-ITP outperforms IC3 [3] in a large number of cases.

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Interpolation-sequence based model checking

Cited by 45 publications

References 15 publications

Efficient modular SAT solving for IC3

Efficient modular SAT solving for IC3

On interpolants and variable assignments

Efficient Generation of Small Interpolants in CNF

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