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Better Predicates and Heuristics for Improved Commutativity Synthesis

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Automated Technology for Verification and Analysis (ATVA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14216))

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Abstract

Code commutativity has increasingly many applications including proof methodologies for concurrency, reductions, automated parallelization, distributed systems and blockchain smart contracts. While there has been some work on automatically generating commutativity conditions through abstraction refinement, the performance of such refinement algorithms critically depends on (i) the universe of predicates and (ii) the choice of the next predicate during search, and thus far this has not been examined in detail.

In this paper, we improve commutativity synthesis by addressing these under-explored requirements. We prune the universe of predicates through a combination of better predicate generation, new a priori syntactic filtering, and through dynamic reduction of the search space. We also present new predicate selection heuristics: one based on look-ahead, and one that utilizes model counting to greedily cover the search space.

Our work is embodied in the new commutativity synthesis tool Servois2, a generational improvement over the state-of-the-art tool Servois. Servois2 is implemented in a faster language and has support for CVC5 and Z3. We contribute new, non-trivial commutativity benchmarks. All of the new features in Servois2 are shown to either increase performance (geomean \(3.58 \times \) speedup) or simplify the conditions generated, when compared against Servois. We also show that our look-ahead heuristic leads to better scaling with respect to the number of predicates.

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Notes

  1. 1.

    https://pldi22.sigplan.org/home/cora-2022.

  2. 2.

    To satisfy closure, we include negations of all predicates. This comes at no performance loss, as such additions can be skipped over by Choose. This is valid because Refine recurses upon the negation of the chosen predicate.

  3. 3.

    https://github.com/veracity-lang/servois2.

  4. 4.

    http://www.veracity-lang.org.

  5. 5.

    mVarA and mVarB are short for multiVarA and multiVarB.

  6. 6.

    http://www.veracity-lang.org.

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Acknowledgements

This work is supported in part by NSF Award #2008633 and #2107169.

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Authors and Affiliations

  1. Stevens Institute of Technology, Hoboken, NJ, USA

    Adam Chen, Parisa Fathololumi, Mihai Nicola, Tegan Brennan & Eric Koskinen

  2. Boston University, Boston, MA, USA

    Jared Pincus

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  1. Adam Chen
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  2. Parisa Fathololumi
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  3. Mihai Nicola
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  4. Jared Pincus
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  6. Eric Koskinen
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Correspondence to Adam Chen .

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Editors and Affiliations

  1. Université Sorbonne Paris Nord, Villetaneuse, France

    Étienne André

  2. Singapore Management University, Singapore, Singapore

    Jun Sun

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Chen, A., Fathololumi, P., Nicola, M., Pincus, J., Brennan, T., Koskinen, E. (2023). Better Predicates and Heuristics for Improved Commutativity Synthesis. In: André, É., Sun, J. (eds) Automated Technology for Verification and Analysis. ATVA 2023. Lecture Notes in Computer Science, vol 14216. Springer, Cham. https://doi.org/10.1007/978-3-031-45332-8_5

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  • DOI: https://doi.org/10.1007/978-3-031-45332-8_5

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