PeRIPLO: A Framework for Producing Effective Interpolants in SAT-Based Software Verification

Rollini, Simone Fulvio; Alt, Leonardo; Fedyukovich, Grigory; Hyvärinen, Antti E. J.; Sharygina, Natasha

doi:10.1007/978-3-642-45221-5_45

Cited by 25 publications

(9 citation statements)

References 22 publications

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“…Interpolation for QF UF is implemented with duality-based interpolation [2], and a similar extension is applied to the interpolation algorithm for QF LRA based on [11]. HiFrog also provides a range of techniques to reduce the size of the generated interpolants through removing redundancies in propositional proofs [13]: (i) the RecyclePivotsWithIntersection (RPI) algorithm, (ii) the LowerUnits (LU) algorithm, (iii) structural hashing (SH), (iv) and a set of local rewriting rules.…”

Section: Tool Overviewmentioning

confidence: 99%

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HiFrog: SMT-based Function Summarization for Software Verification

Alt

Asadi

Chockler

et al. 2017

Lecture Notes in Computer Science

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Abstract. Function summarization can be used as a means of incremental verification based on the structure of the program. HiFrog is a fully featured function-summarization-based model checker that uses SMT as the modeling and summarization language. The tool supports three encoding precisions through SMT: uninterpreted functions, linear real arithmetics, and propositional logic. In addition the tool allows optimized traversal of reachability properties, counter-example-guided summary refinement, summary compression, and user-provided summaries. We describe the use of the tool through the description of its architecture and a rich set of features. The description is complemented by an experimental evaluation on the practical impact the different SMT precisions have on model-checking.

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Section: Tool Overviewmentioning

confidence: 99%

“…We present an implementation of the incremental verification of software with assertions that uses the insights obtained from a successful verification of earlier assertions. As a fundamental building block in storing the insights we use function summaries known to provide speedup through localizing and modularizing verification [9,13].…”

Section: Introductionmentioning

confidence: 99%

HiFrog: SMT-based Function Summarization for Software Verification

Alt

Asadi

Chockler

et al. 2017

Lecture Notes in Computer Science

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“…To the best of our knowledge, there are few conclusive experiments relating interpolant strength with model checking performance. In [47], slight performance improvements are reported when using weak interpolants in the context of bounded model checking with function summaries; however, the results are dominated by improvements achieved when optimising the size of interpolants, preferring smaller over bigger interpolants. In addition, the extraction of different interpolants from the same proof is less flexible than imposing conditions already on the level of proof construction; if a proof does not leverage the right arguments why a program path is infeasible, it is unlikely that good interpolants can be extracted using any method.…”

Section: Related Workmentioning

confidence: 99%

“…Minimisation of proofs and interpolants through proof transformation [46,31,47] can have a positive impact on model checking performance; however, this is mainly due to the reduced overhead when processing smaller formulae, less due to a reduction in the number of refinement steps needed. The same comments as in the previous paragraph apply.…”

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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“…We define the notion of logical strength for LPAISs and show how introducing a partial order over LPAISs allows to systematically compare the strength of the computed interpolants (a feature intuitively relevant to verification since it affects the coarseness of the over-approximations realized by interpolants [12]). We also show how LPAISs can be used to generate collections of interpolants which enjoy the path interpolation (inductive step) property.…”

Section: Introductionmentioning

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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PeRIPLO: A Framework for Producing Effective Interpolants in SAT-Based Software Verification

Cited by 25 publications

References 22 publications

HiFrog: SMT-based Function Summarization for Software Verification

HiFrog: SMT-based Function Summarization for Software Verification

Guiding Craig interpolation with domain-specific abstractions

On interpolants and variable assignments

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