Tree Interpolation in Vampire

Blanc, Régis; Gupta, Ashutosh; Kovács, Laura; Kragl, Bernhard

doi:10.1007/978-3-642-45221-5_13

Cited by 14 publications

(13 citation statements)

References 12 publications

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“…CHCs occur frequently in program verification, and many efficient algorithms for solving CHCs have been developed [Blanc et al 2013;Komuravelli et al 2016;McMillan and Rybalchenko 2013]. In terms of CHC solving, the proof search described in ğ2 is augmented with an extra CHC Realizable =⇒ false, which asserts ¬Realizable.…”

Section: Constrained Horn Clausesmentioning

confidence: 99%

Semantics-guided synthesis

Kim

D’Antoni

et al. 2021

Proc. ACM Program. Lang.

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This paper develops a new framework for program synthesis, called semantics-guided synthesis (SemGuS), that allows a user to provide both the syntax and the semantics for the constructs in the language. SemGuS accepts a recursively defined big-step semantics, which allows it, for example, to be used to specify and solve synthesis problems over an imperative programming language that may contain loops with unbounded behavior. The customizable nature of SemGuS also allows synthesis problems to be defined over a non-standard semantics, such as an abstract semantics. In addition to the SemGuS framework, we develop an algorithm for solving SemGuS problems that is capable of both synthesizing programs and proving unrealizability, by encoding a SemGuS problem as a proof search over Constrained Horn Clauses: in particular, our approach is the first that we are aware of that can prove unrealizabilty for synthesis problems that involve imperative programs with unbounded loops, over an infinite syntactic search space. We implemented the technique in a tool called MESSY, and applied it to SyGuS problems (i.e., over expressions), synthesis problems over an imperative programming language, and synthesis problems over regular expressions.

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Section: Constrained Horn Clausesmentioning

confidence: 99%

Semantics-guided synthesis

Kim

D’Antoni

et al. 2021

Proc. ACM Program. Lang.

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“…Given an unsatisfiable formula ϕ ∧ ψ , a Craig interpolant is another formula χ such that ϕ ⇒ χ is valid and ψ ∧ χ is unsatisfiable. Prior work has proposed many variants of Craig interpolation, including sequence interpolants [Henzinger et al 2004b], tree interpolants [Blanc et al 2013], nested interpolants [Heizmann et al 2010], and DAG interpolants [Albarghouthi et al 2013]. In this paper, we leverage the notion of nested interpolants introduced in Heizmann et al…”

Section: Related Workmentioning

confidence: 99%

Verifying correct usage of context-free API protocols

Ferles

Stephens

Dillig

2021

Proc. ACM Program. Lang.

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Several real-world libraries (e.g., reentrant locks, GUI frameworks, serialization libraries) require their clients to use the provided API in a manner that conforms to a context-free specification. Motivated by this observation, this paper describes a new technique for verifying the correct usage of context-free API protocols. The key idea underlying our technique is to over-approximate the program’s feasible API call sequences using a context-free grammar (CFG) and then check language inclusion between this grammar and the specification. However, since this inclusion check may fail due to imprecision in the program’s CFG abstraction, we propose a novel refinement technique to progressively improve the CFG. In particular, our method obtains counterexamples from CFG inclusion queries and uses them to introduce new non-terminals and productions to the grammar while still over-approximating the program’s relevant behavior. We have implemented the proposed algorithm in a tool called CFPChecker and evaluate it on 10 popular Java applications that use at least one API with a context-free specification. Our evaluation shows that CFPChecker is able to verify correct usage of the API in clients that use it correctly and produces counterexamples for those that do not. We also compare our method against three relevant baselines and demonstrate that CFPChecker enables verification of safety properties that are beyond the reach of existing tools.

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“…In case of the predicate analysis, the refinement procedure computes tree interpolants [20,38] according to procedure scopes, i. e., for each entered (and exited) procedure scope along an infeasible error path, a new subtree for the tree interpolation problem is constructed. For other analyses, like value analysis, the refinement of recursive procedures does not need special handling.…”

Section: Embedding Bam Interprocedural In Cegarmentioning

confidence: 99%