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Detecting Ambiguity in Programming Language Grammars

  • Naveneetha Vasudevan
  • Laurence Tratt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8225)

Abstract

Ambiguous Context Free Grammars (CFGs) are problematic for programming languages, as they allow inputs to be parsed in more than one way. In this paper, we introduce a simple non-deterministic search-based approach to ambiguity detection which non-exhaustively explores a grammar in breadth for ambiguity. We also introduce two new techniques for generating random grammars – Boltzmann sampling and grammar mutation – allowing us to test ambiguity detection tools on much larger corpuses than previously possible. Our experiments show that our breadth-based approach to ambiguity detection performs as well as, and generally better, than extant tools.

Keywords

Main Experiment Mini Experiment Search Base Software Engineering Ambiguous Subset Uniform Random Generation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Naveneetha Vasudevan
    • 1
  • Laurence Tratt
    • 1
  1. 1.Software Development TeamKing’s College LondonUK

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