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Integration, the VLSI Journal
New ideas for solving covering problems
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Solving covering problems using LPR-based lower bounds
DAC '97 Proceedings of the 34th annual Design Automation Conference
GRASP: A Search Algorithm for Propositional Satisfiability
IEEE Transactions on Computers
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
An exact solution to the minimum size test pattern problem
ACM Transactions on Design Automation of Electronic Systems (TODAES)
The Approximability of Constraint Satisfaction Problems
SIAM Journal on Computing
Optimization algorithms for the minimum-cost satisfiability problem
Optimization algorithms for the minimum-cost satisfiability problem
On solving the partial MAX-SAT problem
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Search pruning techniques in SAT-based branch-and-bound algorithms for the binate covering problem
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A fast approximation algorithm for MIN-ONE SAT
Proceedings of the conference on Design, automation and test in Europe
Declarative Infrastructure Configuration Synthesis and Debugging
Journal of Network and Systems Management
Branch and Bound for Boolean Optimization and the Generation of Optimality Certificates
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
Critical Path Selection for Delay Testing Considering Coupling Noise
Journal of Electronic Testing: Theory and Applications
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IEEE Journal on Selected Areas in Communications - Special issue on network infrastructure configuration
Structural relaxations by variable renaming and their compilation for solving MinCostSAT
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
On Computing Backbones of Propositional Theories
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
A novel SAT-based approach to the task graph cost-optimal scheduling problem
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A Framework for Certified Boolean Branch-and-Bound Optimization
Journal of Automated Reasoning
Distilling critical attack graph surface iteratively through minimum-cost SAT solving
Proceedings of the 27th Annual Computer Security Applications Conference
A SAT-based approach to cost-sensitive temporally expressive planning
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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Boolean Satisfiability (SAT) has seen many successful applications in various fields, such as Electronic Design Automation (EDA) and Artificial Intelligence (AI). However, in some cases it may be required/preferable to use variations of the general SAT problem. In this paper we consider one important variation, the Minimum-Cost Satisfiability Problem (MinCostSAT). MinCostSAT is a SAT problem which minimizes the cost of the satisfying assignment. MinCostSAT has various applications, e.g. Automatic Test Pattern Generation (ATPG), FPGA Routing, AI Planning, etc. This problem has been tackled before - first by covering algorithms, e.g. scherzo [3], and more recently by SAT based algorithms, e.g. bsolo [16]. However the SAT algorithms they are based on are not the current generation of highly efficient solvers. The solvers in this generation, e.g. Chaff [20], MiniSat [5] etc., incorporate several new advances, e.g. two literal watching based Boolean Constraint Propagation, that have delivered order of magnitude speedups. We first point out the challenges in using this class of solvers for the MinCostSAT problem and then present techniques to overcome these challenges. The resulting solver MinCostChaff shows order of magnitude improvement over several current best known branch-and-bound solvers for a large class of problems, ranging from Minimum Test Pattern Generation, Bounded Model Checking in EDA to Graph Coloring and Planning in AI.