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An Efficient Algorithm for Learning Event-Recording Automata

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Automated Technology for Verification and Analysis (ATVA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6996))

Abstract

In inference of untimed regular languages, given an unknown language to be inferred, an automaton is constructed to accept the unknown language from answers to a set of membership queries each of which asks whether a string is contained in the unknown language. One of the most well-known regular inference algorithms is the L* algorithm, proposed by Angluin in 1987, which can learn a minimal deterministic finite automaton (DFA) to accept the unknown language. In this work, we propose an efficient polynomial time learning algorithm, TL*, for timed regular language accepted by event-recording automata. Given an unknown timed regular language, TL* first learns a DFA accepting the untimed version of the timed language, and then passively refines the DFA by adding time constraints. We prove the correctness, termination, and minimality of the proposed TL* algorithm.

This research is supported by the research grant MOE2009-T2-1-072 (Advanced Model Checking Systems) in School of Computing, National University of Singapore.

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Author information

Authors and Affiliations

  1. School of Computing, National University of Singapore, Singapore

    Shang-Wei Lin, Étienne André, Jin Song Dong & Yang Liu

  2. Singapore University of Technology and Design, Singapore

    Jun Sun

Authors
  1. Shang-Wei Lin
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  2. Étienne André
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  3. Jin Song Dong
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  4. Jun Sun
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  5. Yang Liu
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Editor information

Editors and Affiliations

  1. University of California, Santa Barbara, CA, USA

    Tevfik Bultan

  2. Department of Computer Science and Information Engineering, National Chung Cheng University, 168 University Road, Min-Hsiung, 62102, Chiayi, Taiwan, ROC

    Pao-Ann Hsiung

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© 2011 Springer-Verlag Berlin Heidelberg

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Lin, SW., André, É., Dong, J.S., Sun, J., Liu, Y. (2011). An Efficient Algorithm for Learning Event-Recording Automata. In: Bultan, T., Hsiung, PA. (eds) Automated Technology for Verification and Analysis. ATVA 2011. Lecture Notes in Computer Science, vol 6996. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24372-1_35

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  • DOI: https://doi.org/10.1007/978-3-642-24372-1_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24371-4

  • Online ISBN: 978-3-642-24372-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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