Efficient implementations of DPLL with the addition of clause learning are the fastest complete satisfiability solvers and can handle many significant real-world problems, such as...
Modern complete SAT solvers almost uniformly implement variations of the clause learning framework introduced by Grasp and Chaff. The success of these solvers has been theoretical...
Currently, the most effective complete SAT solvers are based on the DPLL algorithm augmented by clause learning. These solvers can handle many real-world problems from application...
Philipp Hertel, Fahiem Bacchus, Toniann Pitassi, A...
We study the relative best-case performance of DPLL-based structure-aware SAT solvers in terms of the power of the underlying proof systems. The systems result from (i) varying th...
Abstract. In 1997 we presented ten challenges for research on satisfiability testing [1]. In this paper we review recent progress towards each of these challenges, including our o...
Recently spectacular improvements in the performance of SAT solvers have been achieved through nogood recording (clause learning). In the CSP literature, on the other hand, nogood ...
The techniques for making decisions, i.e., branching, play a central role in complete methods for solving structured CSP instances. In practice, there are cases when SAT solvers be...