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Recovering and Exploiting Structural Knowledge from CNF Formulas
TLDR
A new pre-processing step is proposed in the resolution of SAT instances, that recovers and exploits structural knowledge that is hidden in the CNF to implement a new SAT solver that proves to be the most efficient current one w.r.t. several important classes of instances. Expand
Boosting complete techniques thanks to local search methods
In this paper, an efficient heuristic allowing one to localize inconsistent kernels in propositional knowledge‐bases is described. Then, it is shown that local search techniques can boost theExpand
Local-search Extraction of MUSes
TLDR
A new hybrid technique based on local search is introduced in order to approximate and extract minimally unsatisfiable subformulas (in short, MUSes) of unsatisfiable SAT instances, based on an original counting heuristic grafted to a local search algorithm, which explores the neighborhood of the current interpretation in an original manner, making use of a critical clause concept. Expand
Tabu Search for SAT
TLDR
TSAT, a basic tabu search algonthm for SAT, is introduced and compared with Selman et al. Expand
Boosting a Complete Technique to Find MSS and MUS Thanks to a Local Search Oracle
TLDR
Experimental studies show that this new approach outperforms the best current existing exhaustive ones and makes use of the powerful concept of critical clause and of a computationally inexpensive local search oracle to boost an exhaustive algorithm proposed by Liffiton and Sakallah. Expand
An Experimentally Efficient Method for (MSS, CoMSS) Partitioning
TLDR
A novel algorithm for partitioning a Boolean CNF formula into one MSS and the corresponding CoMSS is introduced, which is more robust and more efficient on most instances than currently available techniques. Expand
Extracting MUSes
TLDR
A new heuristic-based approach to approximate or compute MUSes is presented and it is shown that it often outperforms current competing ones. Expand
On Approaches to Explaining Infeasibility of Sets of Boolean Clauses
TLDR
This paper focuses on the concept of minimally unsatisfiable subformulas (MUSes), which explain logical inconsistency in terms of minimal sets of contradictory clauses, and various recent results and computational approaches about MUSes and related concepts are discussed. Expand
Using local search to find MSSes and MUSes
TLDR
Experimental studies show that this new approach outperforms the best current existing exhaustive ones and makes use of the powerful concept of critical clause and of a computationally inexpensive local search oracle to boost an exhaustive algorithm proposed by Liffiton and Sakallah. Expand
On Freezing and Reactivating Learnt Clauses
TLDR
A new dynamic management policy of the learnt clause database in modern SAT solvers is proposed, based on a dynamic freezing and activation principle of the learned clauses, that activates the most promising learnt clauses while freezing irrelevant ones. Expand
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