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Derivative-Based Diagnosis of Regular Expression Ambiguity

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Implementation and Application of Automata (CIAA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9705))

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Abstract

Regular expressions are often ambiguous. We present a novel method based on Brzozowski’s derivatives to aid the user in diagnosing ambiguous regular expressions. We introduce a derivative-based finite state transducer to generate parse trees and minimal counter-examples. The transducer can be easily customized to either follow the POSIX or Greedy disambiguation policy and based on a finite set of examples it is possible to examine if there are any differences among POSIX and Greedy.

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Notes

  1. 1.

    http://arxiv.org/abs/1604.06644.

  2. 2.

    Additional arguments are x and r but we use notation \({ i njs}_{d_{x}(r)} \ \) to highlight that the definition is defined by pattern match over the various cases of the derivative operation.

  3. 3.

    Technically, we treat the set of parse trees like a list. Recall that \({ a llEps}_{\cdot }\) and the simplification rule (Idemp) favor the left-most match. Alternatives keep their relative position in an expression.

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Acknowledgments

We thank Peter Thiemann and the reviewers for their comments.

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Authors and Affiliations

  1. Faculty of Computer Science and Business Information Systems, Karlsruhe University of Applied Sciences, Moltkestrasse 30, 76133, Karlsruhe, Germany

    Martin Sulzmann

  2. School of Information Technology, Nanyang Polytechnic, 180 Ang Mo Kio Ave 8, Singapore, 569830, Singapore

    Kenny Zhuo Ming Lu

Authors
  1. Martin Sulzmann
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  2. Kenny Zhuo Ming Lu
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Corresponding author

Correspondence to Martin Sulzmann .

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Editors and Affiliations

  1. Yonsei University, Seoul, Korea (Republic of)

    Yo-Sub Han

  2. Queen's University , Kingston, Ontario, Canada

    Kai Salomaa

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Sulzmann, M., Lu, K.Z.M. (2016). Derivative-Based Diagnosis of Regular Expression Ambiguity. In: Han, YS., Salomaa, K. (eds) Implementation and Application of Automata. CIAA 2016. Lecture Notes in Computer Science(), vol 9705. Springer, Cham. https://doi.org/10.1007/978-3-319-40946-7_22

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  • DOI: https://doi.org/10.1007/978-3-319-40946-7_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40945-0

  • Online ISBN: 978-3-319-40946-7

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