An AIG-Based QBF-solver using SAT for preprocessing

Abstract

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 SAT-solvers. 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.