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Maximally-Polyvariant Partial Evaluation in Polynomial Time

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Perspectives of System Informatics (PSI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9609))

Abstract

Maximally-polyvariant partial evaluation is a strategy for program specialization that propagates static values as accurate as possible. The online partial evaluator presented here achieves this precision in time polynomial in the number of partial-evaluation configurations. This is a significant improvement because a conventional partial evaluator can take exponential time, and no fast algorithm was known for maximally-polyvariant specialization. For an important class of quasi-deterministic specialization problems, our algorithm performs in linear time, even for linear-time specialization of a naive string matcher into a linear-time matcher, which was Futamura’s long-standing open challenge. Our results are presented using a recursive flowchart language.

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Notes

  1. 1.

    Multiple return variables; tests are evaluated in the assignment-updated store.

  2. 2.

    A return block that returns to itself halts a program: (spop (return (p) spop)).

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Acknowledgments

The author would like to thank Andrei Klimov and the anonymous reviewers for their comments, and Chung-chieh Shan for discussions of parsing. It is a great pleasure to thank Akihiko Takano for providing the author with excellent working conditions at the National Institute of Informatics, Tokyo, and Masami Hagiya and Zhenjiang Hu for their invaluable support.

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Authors and Affiliations

  1. DIKU, Department of Computer Science, University of Copenhagen, Copenhagen, Denmark

    Robert Glück

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  1. Robert Glück
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Editors and Affiliations

  1. Innopolis University, Innopolis, Russia

    Manuel Mazzara

  2. The University of Manchester, Manchester, United Kingdom

    Andrei Voronkov

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Glück, R. (2016). Maximally-Polyvariant Partial Evaluation in Polynomial Time. In: Mazzara, M., Voronkov, A. (eds) Perspectives of System Informatics. PSI 2015. Lecture Notes in Computer Science(), vol 9609. Springer, Cham. https://doi.org/10.1007/978-3-319-41579-6_11

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  • DOI: https://doi.org/10.1007/978-3-319-41579-6_11

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  • Online ISBN: 978-3-319-41579-6

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