Abstract
We demonstrate that it is fairly easy to decompose any propositional formula into two subsets such that both can be solved by blocked clause elimination. Such a blocked clause decomposition is useful to cheaply detect backbone variables and equivalent literals. Blocked clause decompositions are especially useful when they are unbalanced, i.e., one subset is much larger in size than the other one. We present algorithms and heuristics to obtain unbalanced decompositions efficiently. Our techniques have been implemented in the state-of-the-art solver Lingeling. Experiments show that the performance of Lingeling is clearly improved due to these techniques on application benchmarks of the SAT Competition 2013.
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Heule, M.J.H., Biere, A. (2013). Blocked Clause Decomposition. In: McMillan, K., Middeldorp, A., Voronkov, A. (eds) Logic for Programming, Artificial Intelligence, and Reasoning. LPAR 2013. Lecture Notes in Computer Science, vol 8312. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45221-5_29
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DOI: https://doi.org/10.1007/978-3-642-45221-5_29
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