This contribution contains a fast SAT solver for Isabelle written in Standard ML. By loading the theory DPT SAT Solver, the SAT solver installs itself (under the name “dptsat”) and certain Isabelle tools like Refute will start using it automatically. This is a port of the DPT (Decision Procedure Toolkit) SAT Solver written in OCaml. Theory DPT SAT Tests tests the solver on a few hundred problems.

Propositional Satisfiability (SAT) is a keystone in the history of computer science. SAT was the first problem shown to be NP-complete in 1971 by Stephen Cook [4]. Having passed more than 40 years from then, SAT is now a lively research field where theory and practice have a natural intermixing. In this talk, we overview the use of SAT in practical domains, where SAT is thought in a broad sense...

We analyze, in this work, the performance of a recently introduced weighted Max-SAT solver, Clone, in the Max-SAT evaluation 2007. Clone utilizes a novel bound computation based on formula compilation that allows it to search in a reduced search space. We study how additional techniques from the SAT and Max-SAT literature affect the performance of Clone on problems from the evaluation. We then ...

Combining differing solution approaches by means of solver portfolios has proven as a highly effective technique for boosting solver performance. We consider the problem of generating parallel SAT solver portfolios. Our approach is based on a recently introduced sequential SAT solver portfolio that excelled at the last SAT competition. We show how the approach can be generalized for the paralle...

We analyze to what extent the random SAT and Max-SAT problems differ in their properties. Our findings suggest that for random k-CNF with ratio in a certain range, Max-SAT can be solved by any SAT algorithm with subexponential slowdown, while for formulae with ratios greater than some constant, algorithms under the random walk framework require substantially different heuristics. In light of th...

Recent advances in SAT solvers based on CNF have focused, in particular, on innovative techniques for Boolean constraint propagation (BCP), variable selection, and back-jumping with conflict-driven learning. These techniques have proved to be critical for the high performance of SAT solvers. A great effort by the SAT community has been made to present these SAT techniques clearly and neatly so ...

In a sample of undergraduate students, myopia was associated with higher Math and Total SAT score, and males had higher Math and Total SAT scores than females. The association between myopia and higher Math and Total SAT scores was significant only among males, and the gender differences in Math and Total SAT scores were significant only among allergic participants. There were also significant ...

We present a partial Max-SAT solver QMaxSAT which uses CNF encoding of Boolean cardinality constraints. The old version 0.1 was obtained by adapting a CDCL based SAT solver MiniSat to manage cardinality constraints. It was placed first in the industrial subcategory and second in the crafted subcategory of partial Max-SAT category of the 2010 Max-SAT Evaluation. The new version 0.2 is obtained b...

Many real-world problems are nowadays encoded into SAT instances and efficiently solved by CDCL SAT solvers. However, some scenarios require distributed problem solving approaches. Privacy is often the main reason. This causes the distributed SAT problem. In this work, we analyze how this problem can be tacked in an efficient way, and present ABTSAT, a new version of the ABT algorithm adapted t...

Programs for the Boolean satisfiability problem (SAT), i.e., SAT solvers, are nowadays used as core decision procedures for a wide range of combinatorial problems. Advances in SAT solving during the last 10–15 years have been spurred by yearly solver competitions. In this article, we report on the main SAT solver competition held in 2012, SAT Challenge 2012. Besides providing an overview of how...