Generating Transformers for Deforestation and Supercompilation

Our aim is to study how the interpretive approach — inserting an interpreter between a source program and a program specializer — can be used to improve the transformation of programs and to automatically generate program transformers by self-application of a program specializer. We show that a few semantics-preserving transformations applied to a straightforward interpretive definition of a first-order, call-by-name language are sufficient to generate Wadler’s deforestation algorithm and a version of Turchin’s supercompiler using a partial evaluator. The transformation is guided by the need to binding-time improve the interpreters.