Propositional reasoning (SAT) is an essential part of many reasoning tasks. Many problems in computer science can be compiled to SAT and then effectively decided using state-of-the-art solvers. Alternatively, if reduction to SAT is not feasible, the ideas and technology of state-of-the-art SAT solvers can be useful in deciding the propositional component of the reasoning task being considered. ...

BACKGROUND The development of Graves' disease (GD) after subacute thyroiditis (SAT) is very rare and only a limited number of cases have been reported. OBJECTIVES Here, we report a patient with SAT followed by hypothyroidism and later GD, with ophthalmopathy, occurring 11 years after SAT. CONCLUSION This case illustrates the appearance of thyroid-stimulating hormone (TSH) receptor antibodie...

SAT-based ATPG has proven to be a beneficial complement to traditional ATPG techniques. The generation of a CNF-representation is a vital issue in SAT-based test pattern generation. Firstly, the generation of the problem instances for SAT-based ATPG requires a significant portion of the overall runtime. Secondly, the performance of the SAT solver strongly depends on the properties of the result...

Decision procedures for Boolean satisfiability (SAT), especially modern conflict-driven clause learning (CDCL) solvers, act routinely as core solving engines in various real-world applications. Preprocessing, i.e., applying formula rewriting/simplification rules to the input formula before the actual search for satisfiability, has become an essential part of the SAT solving tool chain. Further,...

There are many combinatorial puzzles around the world. Solving these puzzles is an intellectual challenge to human kinds. In computing, one way of solving these combinatorial puzzles is by modeling them as a satisfiablility problem (SAT). The SAT problem is to find given a propositional logic formula an assignment of the variables which makes the formula true. In this project, we use Sudoku, th...

We present novel branch and bound algorithms for solving Max-SAT and weighted Max-SAT, and provide experimental evidence that outperform the algorithm of Borchers & Furman on Max-2-SAT and weighted Max-2-SAT instances. Our algorithms decrease the time needed to solve an instance, as well as the number of backtracks, up to two orders of magnitude.

Maximum satisfiability (Max-SAT) is more general and more difficult to solve than satisfiability (SAT). In this paper, we first investigate the effectiveness of Walksat, one of the best local search algorithms designed for SAT, on Max-SAT. We show that Walksat is also effective on Max-SAT, while its effectiveness degrades as the problem is more constrained. We then develop a novel method that e...

The rigorous theoretical analyses of algorithms for #SAT have been proposed in the literature. As we know, previous algorithms for solving #SAT have been analyzed only regarding the number of variables as the parameter. However, the time complexity for solving #SAT instances depends not only on the number of variables, but also on the number of clauses. Therefore, it is significant to exploit t...

The rigorous theoretical analyses of algorithms for #SAT have been proposed in the literature. As we know, previous algorithms for solving #SAT have been analyzed only regarding the number of variables as the parameter. However, the time complexity for solving #SAT instances depends not only on the number of variables, but also on the number of clauses. Therefore, it is significant to exploit t...

SAT filters are a novel and compact data structure that can be used to quickly query a word for membership in a fixed set. They have the potential to store more information in a fixed storage limit than a Bloom filter. Constructing a SAT filter requires sampling diverse solutions to randomly constructed constraint satisfaction instances, but there is flexibility in the choice of constraint sati...