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Extended Resolution Proofs for Symbolic SAT Solving with Quantification

机译:随着量化的符号SAT解决方案的扩展分辨率证明

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Symbolic SAT solving is an approach where the clauses of a CNF formula are represented using BDDs. These BDDs are then conjoined, and finally checking satisfiability is reduced to the question of whether the final BDD is identical to false. We present a method combining symbolic SAT solving with BDD quantification (variable elimination) and generation of extended resolution proofs. Proofs are fundamental to many applications, and our results allow the use of BDDs instead of—or in combination with—established proof generation techniques like clause learning. We have implemented a symbolic SAT solver with variable elimination that produces extended resolution proofs. We present details of our implementation, called EBDDRES, which is an extension of the system presented in [1], and also report on experimental results.
机译:符号SAT求解是一种方法,其中CNF公式的子句使用BDD表示。然后将这些BDD联合,最后检查最终BDD是否与错误相同的问题。我们提出了一种用BDD量化(可变消耗)的符号SAT求解以及扩展分辨率样本的产生的方法。证明是许多应用的基础,我们的结果允许使用BDD而不是与既定的证明生成技术相结合,如条款学习。我们已经实现了一个具有可变消除的符号SAT求解器,可产生扩展分辨率样张。我们介绍了我们的实施的详细信息,称为EBDDRES,这是[1]中提供的系统的扩展,也有关于实验结果的报告。

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