Using Minimal Correction Sets to More Efficiently Compute Minimal Unsatisfiable Sets

An unsatisfiable set is a set of formulas whose conjunction is unsatisfiable. Every unsatisfiable set can be corrected, i.e., made satisfiable, by removing a subset of its members. The subset whose removal yields satisfiability is called a correction subset. Given an unsatisfiable set F there is a well known hitting set duality between the unsatisfiable subsets of F and the correction subsets of F: every unsatisfiable subset hits (has a non-empty intersection with) every correction subset, and, dually, every correction subset hits every unsatisfiable subset. An important problem with many applications in practice is to find a minimal unsatisfiable subset (Mus) of F, i.e., an unsatisfiable subset all of whose proper subsets are satisfiable. A number of algorithms for this important problem have been proposed. In this paper we present new algorithms for finding a single MUS and for finding all MUSES. Our algorithms exploit in a new way the duality between correction subsets and unsatisfiable subsets. We show that our algorithms advance the state of the art, enabling more effective computation of MUSES.