On-demand Evaluation by Program Transformation

Strategy annotations are used in eager programming languages (e.g., OBJ2, OBJ3, CafeOBJ, and Maude) for improving efficiency and/or reducing the risk of nontermination. Syntactically, they are given either as lists of natural numbers or as lists of integers associated to function symbols whose (absolute) values refer to the arguments of the corresponding symbol. A positive index forces the evaluation of an argument whereas a negative index means " evaluation on-demand ". Recently, we have developed a formal description of the operational meaning of such on-demand strategy annotations which improves previous formalizations that were lacking satisfactory computational properties. In this paper, we introduce an automatic, semantics–preserving program transformation which produces a program (without negative annotations) which can be then correctly executed by typical OBJ interpreters. Moreover, to demonstrate the practicality of our ideas, the program transformation has been implemented and we compare the behavior of transformed programs with the original ones on a set of representative benchmarks.