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Lazy Reimplication in Chronological Backtracking

Authors Robin Coutelier , Mathias Fleury , Laura Kovács

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LIPIcs.SAT.2024.9.pdf
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Subject Classification

ACM Subject Classification
  • Theory of computation → Constraint and logic programming
  • Theory of computation → Automated reasoning
Keywords
  • Chronological Backtracking
  • CDCL
  • Invariants
  • Watcher Lists

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Abstract

Chronological backtracking is an interesting SAT solving technique within CDCL reasoning, as it backtracks less aggressively upon conflicts. However, chronological backtracking is more difficult to maintain due to its weaker SAT solving invariants. This paper introduces a lazy reimplication procedure for missed lower implications in chronological backtracking. Our method saves propagations by reimplying literals on demand, rather than eagerly. Due to its modularity, our work can be replicated in other solvers, as shown by our results in the solvers CaDiCaL and Glucose.

Cite As Get BibTex

Robin Coutelier, Mathias Fleury, and Laura Kovács. Lazy Reimplication in Chronological Backtracking. In 27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 305, pp. 9:1-9:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.SAT.2024.9

Author Details

Robin Coutelier
  • TU Wien, Austria
Mathias Fleury
  • University Freiburg, Germany
Laura Kovács
  • TU Wien, Austria

Funding

The authors acknowledge support from the ERC Consolidator Grant ARTIST 101002685; the TU Wien Doctoral College TrustACPS; the FWF SpyCoDe SFB projects F8504; the WWTF Grant ForSmart 10.47379/ICT22007; the and the Amazon Research Award 2023 QuAT; the bwHPC of the state of Baden-Württemberg; the German Research Foundation (DFG) through grant INST 35/1597-1 FUGG; and a gift from Intel Corporation.

Acknowledgements

The first author’s Master thesis [Coutelier and others, 2023] conducted at the University of Liège under the supervision of Pascal Fontaine laid the foundations of this work. We thank him for his insights.

Supplementary Materials

References

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