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Automatic Rollback Suggestions for Incremental Datalog Evaluation

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Practical Aspects of Declarative Languages (PADL 2023)

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Abstract

Advances in incremental Datalog evaluation strategies have made Datalog popular among use cases with constantly evolving inputs such as static analysis in continuous integration and deployment pipelines. As a result, new logic programming debugging techniques are needed to support these emerging use cases.

This paper introduces an incremental debugging technique for Datalog, which determines the failing changes for a rollback in an incremental setup. Our debugging technique leverages a novel incremental provenance method. We have implemented our technique using an incremental version of the Soufflé Datalog engine and evaluated its effectiveness on the DaCapo Java program benchmarks analyzed by the Doop static analysis library. Compared to state-of-the-art techniques, we can localize faults and suggest rollbacks with an overall speedup of over 26.9\(\times \) while providing higher quality results.

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Notes

  1. 1.

    We use an Intel Xeon Gold 6130 with 192 GB RAM, GCC 10.3.1, and Python 3.8.10.

  2. 2.

    Available at github.com/davidwzhao/souffle-fault-localization.

  3. 3.

    We say “over” because we bound timeouts to 7200 s.

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Acknowledgments

M.R. was funded by U.S. NSF grants CCF-2146518, CCF-2124431, and CCF-2107261.

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Authors and Affiliations

  1. University of Sydney, Sydney, Australia

    David Zhao & Bernhard Scholz

  2. Microsoft, Redmond, USA

    Pavle Subotić

  3. University Southern California, Los Angeles, USA

    Mukund Raghothaman

Authors
  1. David Zhao
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  2. Pavle Subotić
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  3. Mukund Raghothaman
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  4. Bernhard Scholz
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Corresponding author

Correspondence to David Zhao .

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Editors and Affiliations

  1. University of Kiel, Kiel, Germany

    Michael Hanus

  2. Miami University, Oxford, OH, USA

    Daniela Inclezan

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Zhao, D., Subotić, P., Raghothaman, M., Scholz, B. (2023). Automatic Rollback Suggestions for Incremental Datalog Evaluation. In: Hanus, M., Inclezan, D. (eds) Practical Aspects of Declarative Languages. PADL 2023. Lecture Notes in Computer Science, vol 13880. Springer, Cham. https://doi.org/10.1007/978-3-031-24841-2_19

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  • DOI: https://doi.org/10.1007/978-3-031-24841-2_19

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