Enhancing Partial Deduction via Unfold/Fold Rules

We show that sometimes partial deduction produces poor program specializations because of its limited ability in (i) dealing with conjunctions of recursively deened predicates, (ii) combining partial evaluations of alternative computations, and (iii) taking into account unii-cation failures. We propose to extend the standard partial deduction technique by using versions of the deenition rule and the folding rule which allow us to specialize predicates deened by disjunctions of conjunctions of goals. We also consider a case split rule to take into account uniication failures. Moreover, in order to perform program specialization via partial deduction in an automatic way, we propose a transformation strategy which takes as parameters suitable substrategies for directing the application of every transformation rule. Finally, we show through two examples that our partial deduction technique is superior to standard partial deduction. The rst example refers to the automatic derivation of the Knuth-Morris-Pratt string matching algorithm, and the second example refers to the construction of a parser for a given regular expression. In both examples, the specialized programs are derived starting from naive, non-deterministic initial programs , whereas standard partial deduction can derive similar specialized programs only when complex, deterministic initial programs are provided .