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Data-Oblivious Stream Productivity

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Logic for Programming, Artificial Intelligence, and Reasoning (LPAR 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5330))

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Abstract

We are concerned with demonstrating productivity of specifications of infinite streams of data, based on orthogonal rewrite rules. In general, this property is undecidable, but for restricted formats computable sufficient conditions can be obtained. The usual analysis, also adopted here, disregards the identity of data, thus leading to approaches that we call data-oblivious. We present a method that is provably optimal among all such data-oblivious approaches. This means that in order to improve on our algorithm one has to proceed in a data-aware fashion.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Vrije Universiteit Amsterdam, De Boelelaan 1081a, 1081 HV, Amsterdam, The Netherlands

    Jörg Endrullis & Dimitri Hendriks

  2. Department of Philosophy, Universiteit Utrecht, Heidelberglaan 8, 3584 CS, Utrecht, The Netherlands

    Clemens Grabmayer

Authors
  1. Jörg Endrullis
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  2. Clemens Grabmayer
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  3. Dimitri Hendriks
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Editor information

Editors and Affiliations

  1. Carnegie Mellon University, Doha, Qatar

    Iliano Cervesato

  2. Technische Universität Darmstadt, Germany

    Helmut Veith

  3. University of Manchester, UK

    Andrei Voronkov

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© 2008 Springer-Verlag Berlin Heidelberg

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Endrullis, J., Grabmayer, C., Hendriks, D. (2008). Data-Oblivious Stream Productivity. In: Cervesato, I., Veith, H., Voronkov, A. (eds) Logic for Programming, Artificial Intelligence, and Reasoning. LPAR 2008. Lecture Notes in Computer Science(), vol 5330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89439-1_6

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  • DOI: https://doi.org/10.1007/978-3-540-89439-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89438-4

  • Online ISBN: 978-3-540-89439-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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