Efficient conflict driven learning in a boolean satisfiability solver
Lintao Zhang,Conor F. Madigan,Matthew H. Moskewicz,Sharad Malik +3 more
- pp 279-285
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This paper generalizes various conflict driven learning strategies in terms of different partitioning schemes of the implication graph to re-examine the learning techniques used in various SAT solvers and propose an array of new learning schemes.Abstract:
One of the most important features of current state-of-the-art SAT solvers is the use of conflict based backtracking and learning techniques. In this paper, we generalize various conflict driven learning strategies in terms of different partitioning schemes of the implication graph. We re-examine the learning techniques used in various SAT solvers and propose an array of new learning schemes. Extensive experiments with real world examples show that the best performing new learning scheme has at least a 2/spl times/ speedup compared with learning schemes employed in state-of-the-art SAT solvers.read more
Citations
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Book ChapterDOI
An Extensible SAT-solver
Niklas Een,Niklas Sörensson +1 more
TL;DR: This article presents a small, complete, and efficient SAT-solver in the style of conflict-driven learning, as exemplified by Chaff, and includes among other things a mechanism for adding arbitrary boolean constraints.
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Handbook of Constraint Programming
TL;DR: Researchers from other fields should find in this handbook an effective way to learn about constraint programming and to possibly use some of the constraint programming concepts and techniques in their work, thus providing a means for a fruitful cross-fertilization among different research areas.
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SATzilla: portfolio-based algorithm selection for SAT
TL;DR: SATzilla is described, an automated approach for constructing per-instance algorithm portfolios for SAT that use so-called empirical hardness models to choose among their constituent solvers and is improved by integrating local search solvers as candidate solvers, by predicting performance score instead of runtime, and by using hierarchical hardness models that take into account different types of SAT instances.
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Solving SAT and SAT Modulo Theories: From an abstract Davis--Putnam--Logemann--Loveland procedure to DPLL(T)
TL;DR: Extensive experimental evidence shows that DPLL(T) systems can significantly outperform the other state-of-the-art tools, frequently even in orders of magnitude, and have better scaling properties.
Book ChapterDOI
Satisfiability Modulo Theories
Clark Barrett,Cesare Tinelli +1 more
TL;DR: The architecture of a lazy SMT solver is discussed, examples of theory solvers are given, how to combine such solvers modularly is shown, and several extensions of the lazy approach are mentioned.
References
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