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Mining State-Based Models from Proof Corpora

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Intelligent Computer Mathematics (CICM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8543))

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Abstract

Interactive theorem provers have been used extensively to reason about various software/hardware systems and mathematical theorems. The key challenge when using an interactive prover is finding a suitable sequence of proof steps that will lead to a successful proof requires a significant amount of human intervention. This paper presents an automated technique that takes as input examples of successful proofs and infers an Extended Finite State Machine as output. This can in turn be used to generate proofs of new conjectures. Our preliminary experiments show that the inferred models are generally accurate (contain few false-positive sequences) and that representing existing proofs in such a way can be very useful when guiding new ones.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Leicester, Leicester, UK

    Thomas Gransden, Neil Walkinshaw & Rajeev Raman

Authors
  1. Thomas Gransden
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  2. Neil Walkinshaw
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  3. Rajeev Raman
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Editor information

Editors and Affiliations

  1. Computer Science Department, The University of Western Ontario, MC 375,, N6A 5B7, London, ON, Canada

    Stephen M. Watt

  2. Departments of Computer Science and Mathematical Sciences, University of Bath, Claverton Down, BA2 7AY, Bath, UK

    James H. Davenport

  3. School of Computer Science, Edgbaston, University of Birmingham, B15 2TT, Birmingham, UK

    Alan P. Sexton

  4. Faculty of Informatics, Masaryk University, Botanicá 6a, 60200, Brno, Czech Republic

    Petr Sojka

  5. Institute for Computing Sciences, Radboud University Nijmegen, Postbus 9010,, 6525, Nijmegen, GL, The Netherlands

    Josef Urban

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Gransden, T., Walkinshaw, N., Raman, R. (2014). Mining State-Based Models from Proof Corpora. In: Watt, S.M., Davenport, J.H., Sexton, A.P., Sojka, P., Urban, J. (eds) Intelligent Computer Mathematics. CICM 2014. Lecture Notes in Computer Science(), vol 8543. Springer, Cham. https://doi.org/10.1007/978-3-319-08434-3_21

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  • DOI: https://doi.org/10.1007/978-3-319-08434-3_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08433-6

  • Online ISBN: 978-3-319-08434-3

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