Specialization of Functional Logic Programs Based on Needed Narrowing
Maria Alpuente, Michael Hanus, Salvador Lucas, German Vidal
Abstract
Many functional logic languages are based on narrowing, a unification-based goal-solving mechanism which subsumes the reduction mechanism of functional languages and the resolution principle of logic languages. Needed narrowing is an optimal evaluation strategy which constitutes the basis of modern (narrowing-based) lazy functional logic languages. In this work, we present the fundamentals of partial evaluation in such languages. We provide correctness results for partial evaluation based on needed narrowing and show that the nice properties of this strategy are essential for the specialization process. In particular, the structure of the original program is preserved by partial evaluation and, thus, the same evaluation strategy can be applied for the execution of specialized programs. This is in contrast to other partial evaluation schemes for lazy functional logic programs which may change the program structure in a negative way. Recent proposals for the partial evaluation of declarative multi-paradigm programs use (some form of) needed narrowing to perform computations at partial evaluation time. Therefore, our results constitute the basis for the correctness of such partial evaluators.
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