A semantic matching algorithm: Analysis and implementation

Abstract

A decision procedure for a class of semantic matching problems was proposed in [3], but it yielded efficiency problems, principally because of redundancies. We present in this paper a new semantic matching algorithm for a restricted class of convergent rewrite systems, its theoretical properties, and an efficient implementation. This class of rewrite systems is particularly interesting for functional programming and for program manipulations. To make the algorithm efficient, two techniques are introduced: dependency analysis and sharing analysis. The possibility to divide the semantic matching problems into three complexity classes linear, polynomial, and decidableis also an advantage of our approach. A number of test results shed some light on the efficiency of an ML implementation in the theorem prover Isabelle.KeywordsFunction SymbolMatch ProblemDependency AnalysisInduction AssumptionAutomate DeductionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.