A theory of logic program specialization and generalization for dealing with input data properties

Abstract

We address the problem of specializing logic programs w.r.t. the contexts where they are used. We assume that these contexts are specified by means of computable properties of the input data. We describe a general method by which, given a program P, we can derive a specialized program p1 such that P and P1 are equivalent w.r.t, every input data satisfying a given property. Our method extends the techniques for partial evaluation of logic programs based on Lloyd and Shepherdson’s approach, where a context can only be specified by means of a finite set of bindings for the variables of the input goal. In contrast to most program specialization techniques based on partial evaluation, our method may achieve superlinear speedups, and it does so by using a novel generalization technique.