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Automatic generation of very efficient programs by Generalized Partial Computation

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Wuhan University Journal of Natural Sciences

Abstract

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.

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Authors and Affiliations

  1. Department of Informationr and Computer Science, Waseda University, 3-4-1 Okubo, 169-8555, Shinjuku, Tokyo, Japan

    Yoshihiko Futamura

  2. Institute for Software Production Technology, Waseda University, 3-4-1 Okubo, Shinjuku, 169-8555, Tokyo, Japan

    Zenjiro Konishi & Robert Glück

Authors
  1. Yoshihiko Futamura
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  2. Zenjiro Konishi
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  3. Robert Glück
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Additional information

Biography: Yoshihiko Futamura (1942-), male, Professor, Ph. D., research direction: partial compution,et al.

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Futamura, Y., Konishi, Z. & Glück, R. Automatic generation of very efficient programs by Generalized Partial Computation. Wuhan Univ. J. of Nat. Sci. 6, 1–11 (2001). https://doi.org/10.1007/BF03160221

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  • DOI: https://doi.org/10.1007/BF03160221

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