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An AIG-based QBF-solver using SAT for preprocessing

机译:使用SAT进行预处理的基于AIG的QBF求解器

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In this paper we present a solver for Quantified Boolean Formulas (QBFs) which is based on And-Inverter Graphs (AIGs). We use a new quantifier elimination method for AIGs, which heuristically combines cofactor-based quantifier elimination with quantification using BDDs and thus benefits from the strengths of both data structures. Moreover, we present a novel SAT-based method for preprocessing QBFs that is able to efficiently detect variables with forced truth assignments, allowing for an elimination of these variables from the input formula. We describe the used algorithm which heavily relies on the incremental features of modern SATsolvers. Experimental results demonstrate that our preprocessing method can significantly improve the performance of QBF preprocessing and thus is able to accelerate the overall solving process when used in combination with state-of-the-art QBF-solvers. In particular, we integrated the preprocessing technique as well as the quantifier elimination method into the QBF-solver AIGSolve, allowing it to outperform state-of-the-art solvers.
机译:在本文中,我们提出了基于与反相器图(AIG)的量化布尔公式(QBF)的求解器。我们对AIG使用了一种新的量词消除方法,该方法启发式地将基于辅因子的量词消除与使用BDD的量化结合起来,从而从两种数据结构的优势中受益。此外,我们提出了一种用于预处理QBF的基于SAT的新颖方法,该方法能够有效地检测具有强制真值分配的变量,从而可以从输入公式中消除这些变量。我们描述了所使用的算法,该算法在很大程度上依赖于现代SATsolvers的增量功能。实验结果表明,当与最先进的QBF求解器结合使用时,我们的预处理方法可以显着提高QBF预处理的性能,从而可以加速整个求解过程。特别是,我们将预处理技术以及量词消除方法集成到了QBF求解器AIGSolve中,从而使其性能超过了最新的求解器。

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