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DRAT Proofs for XOR Reasoning

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Logics in Artificial Intelligence (JELIA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10021))

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Abstract

Unsatisfiability proofs in the DRAT format became the de facto standard to increase the reliability of contemporary SAT solvers. We consider the problem of generating proofs for the XOR reasoning component in SAT solvers and propose two methods: direct translation transforms every XOR constraint addition inference into a DRAT proof, whereas T-translation avoids the exponential blow-up in direct translations by using fresh variables. T-translation produces DRAT proofs from Gaussian elimination records that are polynomial in the size of the input CNF formula. Experiments show that a combination of both approaches with a simple prediction method outperforms the BDD-based method.

A. Rebola-Pardo—Supported by the LogiCS doctoral program W1255-N23 of the Austrian Science Fund (FWF), and by the Vienna Science and Technology Fund (WWTF) through grant VRG11-005.

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Notes

  1. 1.

    https://github.com/zhihan/bdd-scala.

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Acknowledgements

We would like to thank an anonymous reviewer who pointed out that the BDD-based approach could be used as a baseline.

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Authors and Affiliations

  1. International Center for Computational Logic, Technische Universität Dresden, 01062, Dresden, Germany

    Tobias Philipp

  2. TU Wien, Wien, Austria

    Adrián Rebola-Pardo

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  1. Tobias Philipp
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  2. Adrián Rebola-Pardo
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Correspondence to Tobias Philipp .

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Editors and Affiliations

  1. Open University of Cyprus, Nicosia, Cyprus

    Loizos Michael

  2. University of Cyprus, Nicosia, Cyprus

    Antonis Kakas

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Philipp, T., Rebola-Pardo, A. (2016). DRAT Proofs for XOR Reasoning. In: Michael, L., Kakas, A. (eds) Logics in Artificial Intelligence. JELIA 2016. Lecture Notes in Computer Science(), vol 10021. Springer, Cham. https://doi.org/10.1007/978-3-319-48758-8_27

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  • DOI: https://doi.org/10.1007/978-3-319-48758-8_27

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