Deductive Generation of Constraint Propagation Rules

Abstract Constraint propagation can often be conveniently expressed by rules. In recent years, a number of techniques for automatic generation of rule-based constraint solvers have been developed, most of them using a generate-and-test approach. We examine a generation method that is based on deduction. A solver (i.e. a set of rules) for a complex constraint is obtained from one or several weaker solvers for simple constraints. We describe incremental solver constructions for several types of constraint modifications, including conjunction, existential and universal quantification.

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