SatEx is a web site devoted to SAT experimentation. It is not only a front end to a database gathering an exhaustive number of executions, but it also allows dynamic results synthesis as well as detailed explorations of experimentation results. Being dynamically generated and constantly updated and improved, this site can be considered as an almost always up-to-date SAT experimentation paper. To the current time, SatEx presents the results of more than 450 CPU days on a recent machine. In a few months, this site has been well received by the SAT community and has reached more than 20000 hits. SatEx site is available at http://www.lri.fr/simon/satex/satex.php3. 1

An algorithm called \Modoc", which has been introduced elsewhere, enhances propositional model elimination with autarky pruning, and other features. The model elimination method is based on linear resolution, and is designed to produce refutations of formulas in conjunctive normal form (CNF). Informally, an autarky is a \self-su cient " model for some clauses, but which does not a ect the remaining clauses of the formula. Modoc nds a model if it fails to nd a refutation, essentially by combining autarkies. Although the original motivation for autarky pruning was to extract a model when the refutation attempt failed, practical experience has shown that it also greatly increases the performance, by reducing the amount of search redundancy. This paper presents a worst-case analysis of Modoc as a function of the number of propositional variables in the formula. The analysis sheds light on why autarky pruning improves the performance, compared to \standard " model elimination. A worst-case analysis of the original algorithm of Davis, Putnam, Loveland and Logemann (DPLL) is also presented. The Modoc analysis yields a worst-case upper bound that is not as strong as the best known upper bound for model-searching satis ability methods, on general propositional CNF. However, it is the rst time a nontrivial upper bound on non-Horn formulas has been shown for any resolution-based refutation procedure.

Resolution has not been an effective tool for deciding satisfiability of propositional CNF formulas, due to explosion of the search space, particularly when the formula is satisfiable. However, a new pruning method, which is designed to eliminate certain refutation attempts that cannot succeed, has been shown to eliminate much of the redundancy of propositional model elimination. The pruning method exploits the concept of "autarky", which was introduced by Monien and Speckenmeyer. Informally, an autarky is a "self-sufficient" model for some clauses, but which does not affect the remaining clauses of the formula. Autarky pruning permits the algorithm, called "Modoc", to be "two-sided" in the sense that it constructs a model if the formula is satisfiable and constructs a refutation proof if it is not. This talk describes new "lemma" and "cut" strategies that are efficient to apply in the setting of propositional resolution. It builds upon the C-literal strategy proposed by Shostak, and s...