Resolution for quantified Boolean formulas
Information and Computation
GRASP—a new search algorithm for satisfiability
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
An algorithm to evaluate quantified Boolean formulae
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Checking equivalence for partial implementations
Proceedings of the 38th annual Design Automation Conference
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Partial Implicit Unfolding in the Davis-Putnam Procedure for Quantified Boolean Formulae
LPAR '01 Proceedings of the Artificial Intelligence on Logic for Programming
Lemma and Model Caching in Decision Procedures for Quantified Boolean Formulas
TABLEAUX '02 Proceedings of the International Conference on Automated Reasoning with Analytic Tableaux and Related Methods
Bounded Model Construction for Monadic Second-Order Logics
CAV '00 Proceedings of the 12th International Conference on Computer Aided Verification
Benefits of Bounded Model Checking at an Industrial Setting
CAV '01 Proceedings of the 13th International Conference on Computer Aided Verification
Conflict driven learning in a quantified Boolean Satisfiability solver
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Learning for quantified boolean logic satisfiability
Eighteenth national conference on Artificial intelligence
Backjumping for quantified Boolean logic satisfiability
Artificial Intelligence
Constructing conditional plans by a theorem-prover
Journal of Artificial Intelligence Research
Using CSP look-back techniques to solve real-world SAT instances
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Clause/term resolution and learning in the evaluation of quantified Boolean formulas
Journal of Artificial Intelligence Research
Symbolic algorithmic verification of generalized noninterference
WSEAS Transactions on Computers
A first step towards a unified proof checker for QBF
SAT'07 Proceedings of the 10th international conference on Theory and applications of satisfiability testing
Nenofex: expanding NNF for QBF solving
SAT'08 Proceedings of the 11th international conference on Theory and applications of satisfiability testing
Proving valid quantified Boolean formulas in HOL light
ITP'11 Proceedings of the Second international conference on Interactive theorem proving
A uniform approach for generating proofs and strategies for both true and false QBF formulas
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
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During the recent years, the development of tools for deciding Quantified Boolean Formulas (QBFs) satisfiability has been accompanied by a steady supply of real-world instances, i.e., QBFs originated by translations from application domains such as formal verification and planning. QBFs from these domains showed to be challenging for current state-of-the-art QBF solvers, and, in order to tackle them, several techniques and even specialized solvers have been proposed. Among these techniques, there are (i) efficient detection and propagation of unit and monotone literals, (ii) branching heuristics that leverages the information extracted during the learning phase, and (iii) look-back techniques based on learning. In this paper we discuss their implementation in our state-of-the-art solver QuBE, pointing out the non trivial issues that arised in the process. We show that all the techniques positively contribute to QuBE performances on average. In particular, we show that monotone literal fixing is the most important technique in order to improve capacity, followed by learning and the heuristics. The situation is reversed if we consider productivity. These and other observations are detailed in the body of the paper. For our analysis, we consider the formal verification and planning benchmarks from the 2003 QBF evaluation.