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Parse Forest Diagnostics with Dr. Ambiguity

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Software Language Engineering (SLE 2011)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6940))

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Abstract

In this paper we propose and evaluate a method for locating causes of ambiguity in context-free grammars by automatic analysis of parse forests. A parse forest is the set of parse trees of an ambiguous sentence. Deducing causes of ambiguity from observing parse forests is hard for grammar engineers because of (a) the size of the parse forests, (b) the complex shape of parse forests, and (c) the diversity of causes of ambiguity.

We first analyze the diversity of ambiguities in grammars for programming languages and the diversity of solutions to these ambiguities. Then we introduce Dr. Ambiguity: a parse forest diagnostics tools that explains the causes of ambiguity by analyzing differences between parse trees and proposes solutions. We demonstrate its effectiveness using a small experiment with a grammar for Java 5.

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Authors and Affiliations

  1. Centrum Wiskunde & Informatica (CWI), Science Park 123, 1098 XG, Amsterdam, The Netherlands

    Hendrikus J. S. Basten & Jurgen J. Vinju

Authors
  1. Hendrikus J. S. Basten
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  2. Jurgen J. Vinju
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Editors and Affiliations

  1. Department of Computing, Macquarie University, 2109, Sydney, NSW, Australia

    Anthony Sloane

  2. Fakultät Informatik, Institut für Software- und Multimediatechnik (SMT), Technische Universität Dresden, Nöthnitzer Straße 46, 01062, Dresden, Germany

    Uwe Aßmann

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Basten, H.J.S., Vinju, J.J. (2012). Parse Forest Diagnostics with Dr. Ambiguity. In: Sloane, A., Aßmann, U. (eds) Software Language Engineering. SLE 2011. Lecture Notes in Computer Science, vol 6940. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28830-2_16

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  • DOI: https://doi.org/10.1007/978-3-642-28830-2_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28829-6

  • Online ISBN: 978-3-642-28830-2

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