Leveraging Interpolant Strength in Model Checking

Rollini, Simone Fulvio; Šerý, Ondřej; Sharygina, Natasha

doi:10.1007/978-3-642-31424-7_18

Cited by 23 publications

(20 citation statements)

References 20 publications

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“…The strength of interpolants can be controlled by choosing different interpolation calculi [18,48], applied to the same propositional resolution proof. To the best of our knowledge, there are few conclusive experiments relating interpolant strength with model checking performance.…”

Section: Related Workmentioning

confidence: 99%

Guiding Craig interpolation with domain-specific abstractions

2015

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PostprintThis is the accepted version of a paper published in Acta Informatica. This paper has been peerreviewed but does not include the final publisher proof-corrections or journal pagination.Citation for the original published paper (version of record):Leroux, J., Rümmer, P., Subotic, P. (2016) Guiding Craig interpolation with domain-specific abstractions. Abstract Craig Interpolation is a standard method to construct and refine abstractions in model checking. To obtain abstractions that are suitable for the verification of software programs or hardware designs, model checkers rely on theorem provers to find the right interpolants, or interpolants containing the right predicates, in a generally infinite lattice of interpolants for any given interpolation problem. We present a semantic and solver-independent framework for systematically exploring interpolant lattices, based on the notion of interpolation abstraction. We discuss how interpolation abstractions can be constructed for a variety of logics, and how they can be applied in the context of software model checking.

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Section: Related Workmentioning

confidence: 99%

Guiding Craig interpolation with domain-specific abstractions

2015

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“…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. In this subsection we study conditions for labeling functions that have to be satisfied in order to guarantee the PI property of interpolant sequences generated by LPAISs.…”

Section: B Path Interpolation Propertymentioning

confidence: 99%

“…For LISs, [13] defines a set of labeling constraints on the labeling functions used to compute the interpolants I and I ; if the labeling constraints are satisfied, the interpolants have the PI property. However, we prove the PI property in another way, more suitable for LPAISs.…”

Section: B Path Interpolation Propertymentioning

confidence: 99%

“…A single solver call results in a single proof from which all the interpolants for the sub-problems are computed. The presence of a single proof, in turn, enables (ii) generating collections of interpolants which satisfy properties relevant to verification, such as path interpolation [7], [13]. Such collections are hard to obtain if multiple proofs are involved.…”

Section: Introductionmentioning

confidence: 99%

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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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“…In practice, additional properties of multiple interpolants generated from a single unsatisfiable formula are often required, resulting in path interpolants and tree interpolants. Note that it is often possible to ensure these additional properties by careful construction of interpolants from the same proof of unsatisfiability [15]. In the implementation of eVolCheck algorithms, the tree interpolant property is essential as it must be satisfied to maintain valid function summaries and to ensure the correctness of the overall local upgrade checking.…”

Section: Background Theorymentioning

confidence: 99%

eVolCheck: Incremental Upgrade Checker for C

Fedyukovich

Šerý

Sharygina

2013

Tools and Algorithms for the Construction and Analysis of Systems

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Software is not created at once. Rather, it grows incrementally version by version and evolves long after being first released. To be practical for software developers, the software verification tools should be able to cope with changes. In this paper, we present a tool, eVolCheck, that focuses on incremental verification of software as it evolves. During the software evolution the tool maintains abstractions of program functions, function summaries, derived using Craig interpolation. In each check, the function summaries are used to localize verification of an upgrade to analysis of the modified functions. Experimental evaluation on a range of various benchmarks shows substantial speedup of incremental upgrade checking of eVolCheck in contrast to checking each version from scratch.

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Leveraging Interpolant Strength in Model Checking

Cited by 23 publications

References 20 publications

Guiding Craig interpolation with domain-specific abstractions

Guiding Craig interpolation with domain-specific abstractions

On interpolants and variable assignments

eVolCheck: Incremental Upgrade Checker for C

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