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Automated Reencoding of Boolean Formulas

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Hardware and Software: Verification and Testing (HVC 2012)

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Abstract

We present a novel preprocessing technique to automatically reduce the size of Boolean formulas. This technique, called Bounded Variable Addition (BVA), exchanges clauses for variables. Similar to other preprocessing techniques, BVA greedily lowers the sum of variables and clauses, a rough measure for the hardness to solve a formula. We show that cardinality constraints (CCs) can efficiently be reencoded: from a naive CC encoding, BVA automatically generates a compact encoding, which is smaller than sophisticated encodings. Experimental results show that applying BVA can improve SAT solving performance.

The second and the third author are supported by the Austrian Science Foundation (FWF) NFN Grant S11408-N23 (RiSE). The second author is supported by DARPA contract number N66001-10-2-4087.

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Author information

Authors and Affiliations

  1. Institute of Artificial Intelligence, Technische Universität Dresden, Germany

    Norbert Manthey

  2. Department of Computer Science, The University of Texas at Austin, USA

    Marijn J. H. Heule

  3. Institute for Formal Models and Verification, Johannes Kepler University, Austria

    Marijn J. H. Heule & Armin Biere

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  1. Norbert Manthey
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  2. Marijn J. H. Heule
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  3. Armin Biere
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Editors and Affiliations

  1. Institute for Formal Models and Verification, Johannes Kepler University, Linz, Austria

    Armin Biere

  2. IBM Research Laboratory, 31905, Haifa, Israel

    Amir Nahir

  3. Universidad Politecnica de Valencia, 46022, Valencia, Spain

    Tanja Vos

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Manthey, N., Heule, M.J.H., Biere, A. (2013). Automated Reencoding of Boolean Formulas. In: Biere, A., Nahir, A., Vos, T. (eds) Hardware and Software: Verification and Testing. HVC 2012. Lecture Notes in Computer Science, vol 7857. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39611-3_14

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  • DOI: https://doi.org/10.1007/978-3-642-39611-3_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39610-6

  • Online ISBN: 978-3-642-39611-3

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