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Modular Multiset Rewriting

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Book cover Logic for Programming, Artificial Intelligence, and Reasoning (LPAR 2015)

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Abstract

Rule-based languages are being used for ever more ambitious applications. As program size grows however, so does the overhead of team-based development, reusing components, and just keeping a large flat collection of rules from interfering. In this paper, we propose a module system for a small logically-motivated rule-based language. The resulting modules are nothing more than rewrite rules of a specific form, which are themselves just logic formulas. Yet, they provide some of the same features found in advanced module systems such as that of Standard ML, in particular name space separation, support for abstract data types, and parametrization (functors in ML). Our modules also offer essential features for concurrent programming such as facilities for sharing private names. This approach is directly applicable to other rule-based languages, including most forward-chaining logic programming languages and many process algebras.

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Acknowledgments

This paper was made possible by grants NPRP 09-667-1-100 (Effective Programming for Large Distributed Ensembles) and NPRP 4-341-1-059 (Usable automated data inference for end-users) from the Qatar National Research Fund (a member of the Qatar Foundation). The statements made herein are solely the responsibility of the authors.

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Authors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Iliano Cervesato & Edmund S. L. Lam

Authors
  1. Iliano Cervesato
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  2. Edmund S. L. Lam
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Corresponding author

Correspondence to Iliano Cervesato .

Editor information

Editors and Affiliations

  1. New York University, New York, New York, USA

    Martin Davis

  2. University of the South Pacific, Suva, Fiji

    Ansgar Fehnker

  3. Macquarie University, Sydney, New South Wales, Australia

    Annabelle McIver

  4. The University of Manchester, Manchester, United Kingdom

    Andrei Voronkov

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Cervesato, I., Lam, E.S.L. (2015). Modular Multiset Rewriting. In: Davis, M., Fehnker, A., McIver, A., Voronkov, A. (eds) Logic for Programming, Artificial Intelligence, and Reasoning. LPAR 2015. Lecture Notes in Computer Science(), vol 9450. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48899-7_36

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  • DOI: https://doi.org/10.1007/978-3-662-48899-7_36

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-48898-0

  • Online ISBN: 978-3-662-48899-7

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