A Structure-preserving Clause Form Translation
Journal of Symbolic Computation
QUBE: A System for Deciding Quantified Boolean Formulas Satisfiability
IJCAR '01 Proceedings of the First International Joint Conference on Automated Reasoning
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
A solver for QBFs in negation normal form
Constraints
Solving QBF with combined conjunctive and disjunctive normal form
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Blocked clause elimination for QBF
CADE'11 Proceedings of the 23rd international conference on Automated deduction
SAT'04 Proceedings of the 7th international conference on Theory and Applications of Satisfiability Testing
A non-prenex, non-clausal QBF solver with game-state learning
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
QBF modeling: exploiting player symmetry for simplicity and efficiency
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Recovering and utilizing partial duality in QBF
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
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Conjunctive Normal Form (CNF) representation as used by most modern Quantified Boolean Formula (QBF) solvers is simple and powerful when reasoning about conflicts, but is not efficient at dealing with solutions. To overcome this inefficiency a number of specialized non-CNF solvers were created. These solvers were shown to have great advantages. Unfortunately, non-CNF solvers cannot benefit from sophisticated CNF-based techniques developed over the years. This paper demonstrates how the power of non-CNF structure can be harvested without the need for specialized solvers; in fact, it is easily incorporated into most existing CNF-based QBF solvers using a pre-existing mechanism of cube learning. We demonstrate this using a state-of-the-art QBF solver DepQBF, and experimentally show the effectiveness of our approach.