Separation logic for sequential programs (functional pearl)

Charguéraud, Arthur

doi:10.1145/3408998

Cited by 21 publications

(17 citation statements)

References 84 publications

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“…In this way, the process of implementing the translation was not strongly tied to the choice of benchmarks, with only a few examples needed to test the implementation of the rules before the entire milestone would be implemented. The fact that we saw the same milestones across all backends suggests that our experience will generalise to other targets (Charguéraud 2020;Chlipala 2011).…”

Section: Lessons Learntmentioning

confidence: 51%

Certifying the synthesis of heap-manipulating programs

Watanabe

Gopinathan

Pîrlea

et al. 2021

Proc. ACM Program. Lang.

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Automated deductive program synthesis promises to generate executable programs from concise specifications, along with proofs of correctness that can be independently verified using third-party tools. However, an attempt to exercise this promise using existing proof-certification frameworks reveals significant discrepancies in how proof derivations are structured for two different purposes: program synthesis and program verification. These discrepancies make it difficult to use certified verifiers to validate synthesis results, forcing one to write an ad-hoc translation procedure from synthesis proofs to correctness proofs for each verification backend. In this work, we address this challenge in the context of the synthesis and verification of heap-manipulating programs. We present a technique for principled translation of deductive synthesis derivations (a.k.a. source proofs) into deductive target proofs about the synthesised programs in the logics of interactive program verifiers. We showcase our technique by implementing three different certifiers for programs generated via SuSLik, a Separation Logic-based tool for automated synthesis of programs with pointers, in foundational verification frameworks embedded in Coq: Hoare Type Theory (HTT), Iris, and Verified Software Toolchain (VST), producing concise and efficient machine-checkable proofs for characteristic synthesis benchmarks.

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Section: Lessons Learntmentioning

confidence: 51%

Certifying the synthesis of heap-manipulating programs

Watanabe

Gopinathan

Pîrlea

et al. 2021

Proc. ACM Program. Lang.

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“…Finally, let ⊤ ⊤ be an aine top [5], i.e., an assertion with ⊢ ⊤ ⊤ and ⊤ ⊤ ⋆ ⊤ ⊤ = ⊤ ⊤, which captures resources that can be safely discarded. We deine the Hoare triple {P} c {Q} to hold if:…”

Section: Reasoning Setupmentioning

confidence: 99%

For a Few Dollars More: Verified Fine-Grained Algorithm Analysis Down to LLVM

Haslbeck

Lammich

2022

ACM Trans. Program. Lang. Syst.

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We present a framework to verify both, functional correctness and (amortized) worst-case complexity of practically efficient algorithms. We implemented a stepwise refinement approach, using the novel concept of resource currencies to naturally structure the resource analysis along the refinement chain, and allow a fine-grained analysis of operation counts. Our framework targets the LLVM intermediate representation. We extend its semantics from earlier work with a cost model. As case studies, we verify the amortized constant time push operation on dynamic arrays and the O ( n log n ) introsort algorithm, and refine them down to efficient LLVM implementations. Our sorting algorithm performs on par with the state-of-the-art implementation found in the GNU C++ Library, and provably satisfies the complexity required by the C++ standard.

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“…Regarding the semantics of an inductive heap predicate, we follow the standard least fixed point semantics [1] by interpreting an inductive predicate symbol P as the least fixed point P of a monotone operator constructed from its inductive definition. We follow the literature to use separation logic [5,19,44] to verify the functional correctness of a program w.r.t. its specification.…”

Section: Program Verification Using Separation Logicmentioning

confidence: 99%

“…In this section, we do not present separation logic rules due to the page limit. Interested readers could refer to [5,19,44].…”

Section: Program Verification Using Separation Logicmentioning

confidence: 99%

Automated Repair of Heap-Manipulating Programs Using Deductive Synthesis

Nguyen

Sergey

et al. 2021

Lecture Notes in Computer Science

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We propose a novel method to automatically repairing buggy heap-manipulating programs using constraint solving and deductive synthesis. Given an input program C and its formal specification in the form of a Hoare triple: {P} C {Q}, we use a separation-logic-based verifier to verify if program C is correct w.r.t. its specifications. If program C is found buggy, we then repair it in the following steps. First, we rely on the verification results to collect a list of suspicious statements of the buggy program. For each suspicious statement, we temporarily replace it with a template patch representing the desired statements. The template patch is also formally specified using a pair of unknown pre-and postcondition. Next, we use the verifier to analyze the temporarily patched program to collect constraints related to the pre-and postcondition of the template patch. Then, these constraints are solved by our constraint solving technique to discover the suitable specifications of the template patch. Subsequently, these specifications can be used to synthesize program statements of the template patch, consequently creating a candidate program. Finally, if the candidate program is validated, it is returned as the repaired program. We demonstrate the effectiveness of our approach by evaluating our implementation and a state-of-the-art approach on a benchmark of 231 buggy programs. The experimental results show that our tool successfully repairs 223 buggy programs and considerably outperforms the compared tool.

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Separation logic for sequential programs (functional pearl)

Cited by 21 publications

References 84 publications

Certifying the synthesis of heap-manipulating programs

Certifying the synthesis of heap-manipulating programs

For a Few Dollars More: Verified Fine-Grained Algorithm Analysis Down to LLVM

Automated Repair of Heap-Manipulating Programs Using Deductive Synthesis

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