Guiding Craig interpolation with domain-specific abstractions

Leroux, Jérôme; Rümmer, Philipp; Subotić, Pavle

doi:10.1007/s00236-015-0236-z

Cited by 19 publications

(26 citation statements)

References 58 publications

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“…Eldarica uses interpolation abstraction [18] as a semantic way to guide the interpolation procedure towards "good" interpolants; in this method, interpolation queries are instrumented to restrict the symbols that can occur in interpolants, ranking the interpolants with the help of templates. It has previously been shown that interpolation abstraction can significantly improve the performance of Horn solvers [18].…”

Section: Craig Interpolation With Templatesmentioning

confidence: 99%

“…Picking the right predicates, either upfront or dynamically during analysis [5], is essential in this setting to ensure rapid convergence of a model checker, and is in practice achieved through a combination of "systematic" methods (for CEGAR, in particular through Craig interpolation) and heuristics. For instance, SLAM extracts refinement predicates from counterexamples using domain-specific heuristics [16]; YOGI uses machine learning to choose the default set of heuristics for picking predicates [19]; CPAchecker uses domain types to decide whether to represent variables explicitly or using BDDs [2], and to choose refinement predicates [4]; and Eldarica uses heuristics to guide the process of Craig interpolation [18]. Similar heuristics can be identified in tools based on abstract interpretation, among others.…”

Section: Introductionmentioning

confidence: 99%

“…Eldarica has two main parameters controlling the analysis process: initial predicates for predicate abstraction, and templates guiding Craig interpolation during counterexamplebased refinement [18]. Both parameters can be provided in the form of sourcecode annotations.…”

Section: Introductionmentioning

confidence: 99%

“…This research in particular considers various methods of Craig interpolation, and controls features such as interpolant strength, interpolant size, the number of distinct symbols in interpolants, or syntactic features like the magnitude of coefficients; for a detailed survey we refer the reader to our previous work [18].…”

Section: Introductionmentioning

confidence: 99%

“…As demonstrated by this example, heuristics are needed to guide interpolation towards finding suitable refinement predicates. The community has suggested various heuristics for the above example, e.g., the most recent version of Eldarica [18] proves the program safe in 5 sec and 6 CEGAR iterations.…”

Section: Introductory Examples Of Domain-specific Abstractionmentioning

confidence: 99%

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Systematic Predicate Abstraction Using Variable Roles

Demyanova

Rümmer

Zuleger

2017

Lecture Notes in Computer Science

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Abstract. Heuristics for discovering predicates for abstraction are an essential part of software model checkers. Picking the right predicates affects the runtime of a model checker, or determines if a model checker is able to solve a verification task at all. In this paper we present a method to systematically specify heuristics for generating program-specific abstractions. The heuristics can be used to generate initial abstractions, and to guide abstraction refinement through templates provided for Craig interpolation. We describe the heuristics using variable roles, which allow us to pick domain-specific predicates according to the program under analysis. Variable roles identify typical variable usage patterns and can be computed using lightweight static analysis, for instance with the help of of-the-shelf logical programming engines. We implemented a prototype tool which extracts initial predicates and templates for C programs and passes them to the Eldarica model checker in the form of source code annotations. For evaluation, we defined a set of heuristics, motivated by Eldarica's previous built-in heuristics and typical verification benchmarks from the literature and SV-COMP. We evaluate our approach on a set of more than 500 programs, and observe an overall increase in the number of solved tasks by 11.2%, and significant speedup on certain benchmark families.

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Section: Craig Interpolation With Templatesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductory Examples Of Domain-specific Abstractionmentioning

confidence: 99%

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Systematic Predicate Abstraction Using Variable Roles

Demyanova

Rümmer

Zuleger

2017

Lecture Notes in Computer Science

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Global Guidance for Local Generalization in Model Checking

Krishnan

Chen

Shoham

et al. 2020

Computer Aided Verification

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SMT-based model checkers, especially IC3-style ones, are currently the most effective techniques for verification of infinite state systems. They infer global inductive invariants via local reasoning about a single step of the transition relation of a system, while employing SMTbased procedures, such as interpolation, to mitigate the limitations of local reasoning and allow for better generalization. Unfortunately, these mitigations intertwine model checking with heuristics of the underlying SMT-solver, negatively affecting stability of model checking. In this paper, we propose to tackle the limitations of locality in a systematic manner. We introduce explicit global guidance into the local reasoning performed by IC3-style algorithms. To this end, we extend the SMT-IC3 paradigm with three novel rules, designed to mitigate fundamental sources of failure that stem from locality. We instantiate these rules for the theory of Linear Integer Arithmetic and implement them on top of Spacer solver in Z3. Our empirical results show that GSpacer, Spacer extended with global guidance, is significantly more effective than both Spacer and sole global reasoning, and, furthermore, is insensitive to interpolation.

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