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Revisiting Hyper Binary Resolution

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7874)

Abstract

This paper focuses on developing efficient inference techniques for improving conjunctive normal form (CNF) Boolean satisfiability (SAT) solvers. We analyze a variant of hyper binary resolution from various perspectives: We show that it can simulate the circuit-level technique of structural hashing and how it can be realized efficiently using so called tree-based lookahead. Experiments show that our implementation improves the performance of state-of-the-art CNF-level SAT techniques on combinational equivalent checking instances.

The first author is supported by DARPA contract number N66001-10-2-4087. The first and third authors are supported by Austrian Science Foundation (FWF) NFN Grant S11408-N23 (RiSE), and the second author by Academy of Finland (grants 132812 and 251170).

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Heule, M.J.H., Järvisalo, M., Biere, A. (2013). Revisiting Hyper Binary Resolution. In: Gomes, C., Sellmann, M. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2013. Lecture Notes in Computer Science, vol 7874. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38171-3_6

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  • DOI: https://doi.org/10.1007/978-3-642-38171-3_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38170-6

  • Online ISBN: 978-3-642-38171-3

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