Abstract
A propositional formula in Conjunctive Normal Form (CNF) may contain redundant clauses — clauses whose removal from the formula does not affect the set of its models. Identification of redundant clauses is important because redundancy often leads to unnecessary computation, wasted storage, and may obscure the structure of the problem. A formula obtained by the removal of all redundant clauses from a given CNF formula \({\mathcal{F}}\) is called a Minimal Equivalent Subformula (MES) of \({\mathcal{F}}\). This paper proposes a number of efficient algorithms and optimization techniques for the computation of MESes. Previous work on MES computation proposes a simple algorithm based on iterative application of the definition of a redundant clause, similar to the well-known deletion-based approach for the computation of Minimal Unsatisfiable Subformulas (MUSes). This paper observes that, in fact, most of the existing algorithms for the computation of MUSes can be adapted to the computation of MESes. However, some of the optimization techniques that are crucial for the performance of the state-of-the-art MUS extractors cannot be applied in the context of MES computation, and thus the resulting algorithms are often not efficient in practice. To address the problem of efficient computation of MESes, the paper develops a new class of algorithms that are based on the iterative analysis of subsets of clauses. The experimental results, obtained on representative problem instances, confirm the effectiveness of the proposed algorithms. The experimental results also reveal that many CNF instances obtained from the practical applications of SAT exhibit a large degree of redundancy.
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References
Atserias, A., Fichte, J.K., Thurley, M.: Clause-learning algorithms with many restarts and bounded-width resolution. J. Artif. Intell. Res. 40, 353–373 (2011)
Ausiello, G., D’Atri, A., Saccà, D.: Minimal representation of directed hypergraphs. SIAM J. Comput. 15(2), 418–431 (1986)
Bakker, R.R., Dikker, F., Tempelman, F., Wognum, P.M.: Diagnosing and solving over-determined constraint satisfaction problems. In: IJCAI, pp. 276–281 (1993)
Belov, A., Marques-Silva, J.: Accelerating MUS extraction with recursive model rotation. In: FMCAD, pp. 37–40 (2011)
Biere, A.: Picosat essentials. Journal on Satisfiability, Boolean Modeling and Computation 4, 75–97 (2008)
Biere, A., Heule, M., van Maaren, H., Walsh, T. (eds.): Handbook of Satisfiability. Frontiers in Artificial Intelligence and Applications, vol. 185. IOS Press (2009)
Boufkhad, Y., Roussel, O.: Redundancy in random SAT formulas. In: AAAI, pp. 273–278 (2000)
Chinneck, J.W., Dravnieks, E.W.: Locating minimal infeasible constraint sets in linear programs. INFORMS Journal on Computing 3(2), 157–168 (1991)
Chmeiss, A., Krawczyk, V., Sais, L.: Redundancy in CSPs. In: ECAI, pp. 907–908 (2008)
Choi, C.W., Lee, J.H.-M., Stuckey, P.J.: Removing propagation redundant constraints in redundant modeling. ACM Trans. Comput. Log. 8(4) (2007)
de Siqueira, N.J.L., Puget, J.-F.: Explanation-based generalisation of failures. In: ECAI, pp. 339–344 (1988)
Dechter, A., Dechter, R.: Removing redundancies in constraint networks. In: AAAI, pp. 105–109 (1987)
Dershowitz, N., Hanna, Z., Nadel, A.: A Scalable Algorithm for Minimal Unsatisfiable Core Extraction. In: Biere, A., Gomes, C.P. (eds.) SAT 2006. LNCS, vol. 4121, pp. 36–41. Springer, Heidelberg (2006)
Desrosiers, C., Galinier, P., Hertz, A., Paroz, S.: Using heuristics to find minimal unsatisfiable subformulas in satisfiability problems. J. Comb. Optim. 18(2), 124–150 (2009)
Fourdrinoy, O., Grégoire, É., Mazure, B., Saïs, L.: Eliminating Redundant Clauses in SAT Instances. In: Van Hentenryck, P., Wolsey, L.A. (eds.) CPAIOR 2007. LNCS, vol. 4510, pp. 71–83. Springer, Heidelberg (2007)
González, S.M., Meseguer, P.: Boosting MUS Extraction. In: Miguel, I., Ruml, W. (eds.) SARA 2007. LNCS (LNAI), vol. 4612, pp. 285–299. Springer, Heidelberg (2007)
Grégoire, É., Mazure, B., Piette, C.: MUST: Provide a Finer-Grained Explanation of Unsatisfiability. In: Bessière, C. (ed.) CP 2007. LNCS, vol. 4741, pp. 317–331. Springer, Heidelberg (2007)
Grégoire, É., Mazure, B., Piette, C.: On approaches to explaining infeasibility of sets of Boolean clauses. In: ICTAI, pp. 74–83 (November 2008)
Grimm, S., Wissmann, J.: Elimination of Redundancy in Ontologies. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part I. LNCS, vol. 6643, pp. 260–274. Springer, Heidelberg (2011)
Hammer, P.L., Kogan, A.: Optimal compression of propositional horn knowledge bases: Complexity and approximation. Artif. Intell. 64(1), 131–145 (1993)
Hemery, F., Lecoutre, C., Sais, L., Boussemart, F.: Extracting MUCs from constraint networks. In: ECAI, pp. 113–117 (2006)
Järvisalo, M., Heule, M.J.H., Biere, A.: Inprocessing Rules. In: Gramlich, B., Miller, D., Sattler, U. (eds.) IJCAR 2012. LNCS, vol. 7364, pp. 355–370. Springer, Heidelberg (2012)
Junker, U.: QUICKXPLAIN: Preferred explanations and relaxations for over-constrained problems. In: AAAI, pp. 167–172 (2004)
Kullmann, O.: Constraint satisfaction problems in clausal form II: Minimal unsatisfiability and conflict structure. Fundam. Inform. 109(1), 83–119 (2011)
Liberatore, P.: Redundancy in logic I: CNF propositional formulae. Artif. Intell. 163(2), 203–232 (2005)
Liffiton, M.H., Sakallah, K.A.: Algorithms for computing minimal unsatisfiable subsets of constraints. J. Autom. Reasoning 40(1), 1–33 (2008)
Marques-Silva, J.: Minimal unsatisfiability: Models, algorithms and applications. In: ISMVL, pp. 9–14 (2010)
Marques-Silva, J., Lynce, I.: On Improving MUS Extraction Algorithms. In: Sakallah, K.A., Simon, L. (eds.) SAT 2011. LNCS, vol. 6695, pp. 159–173. Springer, Heidelberg (2011)
Nadel, A.: Boosting minimal unsatisfiable core extraction. In: FMCAD, pp. 121–128 (October 2010)
Niepert, M., Gucht, D.V., Gyssens, M.: Logical and algorithmic properties of stable conditional independence. Int. J. Approx. Reasoning 51(5), 531–543 (2010)
Piette, C.: Let the solver deal with redundancy. In: ICTAI, pp. 67–73 (2008)
Piette, C., Hamadi, Y., Saïs, L.: Efficient Combination of Decision Procedures for MUS Computation. In: Ghilardi, S., Sebastiani, R. (eds.) FroCoS 2009. LNCS, vol. 5749, pp. 335–349. Springer, Heidelberg (2009)
Pipatsrisawat, K., Darwiche, A.: On the power of clause-learning SAT solvers as resolution engines. Artif. Intell. 175(2), 512–525 (2011)
Plaisted, D.A., Greenbaum, S.: A structure-preserving clause form translation. Journal of Symbolic Computation 2(3), 293–304 (1986)
Scholl, C., Disch, S., Pigorsch, F., Kupferschmid, S.: Computing Optimized Representations for Non-convex Polyhedra by Detection and Removal of Redundant Linear Constraints. In: Kowalewski, S., Philippou, A. (eds.) TACAS 2009. LNCS, vol. 5505, pp. 383–397. Springer, Heidelberg (2009)
To, S.T., Son, T.C., Pontelli, E.: On the use of prime implicates in conformant planning. In: AAAI (2010)
To, S.T., Son, T.C., Pontelli, E.: Conjunctive representations in contingent planning: Prime implicates versus minimal CNF formula. In: AAAI (2011)
van Maaren, H., Wieringa, S.: Finding Guaranteed MUSes Fast. In: Kleine Büning, H., Zhao, X. (eds.) SAT 2008. LNCS, vol. 4996, pp. 291–304. Springer, Heidelberg (2008)
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Belov, A., Janota, M., Lynce, I., Marques-Silva, J. (2012). On Computing Minimal Equivalent Subformulas. In: Milano, M. (eds) Principles and Practice of Constraint Programming. CP 2012. Lecture Notes in Computer Science, vol 7514. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33558-7_14
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