Discovery of Minimal Unsatisfiable Subsets of Constraints Using Hitting Set Dualization

An unsatisfiable set of constraints is minimal if all its (strict) subsets are satisfiable. The task of type error diagnosis requires finding all minimal unsatisfiable subsets of a given set of constraints (representing an error), in order to generate the best explanation of the error. Similarly circuit error diagnosis requires finding all minimal unsatisfiable subsets in order to make minimal diagnoses. In this paper we present a new approach for efficiently determining all minimal unsatisfiable sets for any kind of constraints. Our approach makes use of the duality that exists between minimal unsatisfiable constraint sets and maximal satisfiable constraint sets. We show how to incrementally compute both these sets, using the fact that the complements of the maximal satisfiable constraint sets are the hitting sets of the minimal unsatisfiable constraint sets. We experimentally compare our technique to the best known method on a number of large type problems and show that considerable improvements in running time are obtained.