Automatic Generation of Very Efficient Programs by Generalized Partial Computation

摘要

Generalized Partial Computation (GPC) is a program transformation method utilizing partial information about input data, properties of auxiliary functions and the logical structure of a source program. GPC uses both an inference engine such as a theorem prover and a classical partial evaluator to optimize programs. Therefore, GPC is more powerful than classical partial evaluators but harder to implement and control. We have implemented an experimental GPC system called WSDFU (Waseda Simplify Distribute Fold Unfold). This paper discusses the power of the program transformation system, its theorem prover and future works.