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AALpy: An Active Automata Learning Library

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Automated Technology for Verification and Analysis (ATVA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12971))

Abstract

AALpy is an extensible open-source Python library providing efficient implementations of active automata learning algorithms for deterministic, non-deterministic, and stochastic systems. We put a special focus on the conformance testing aspect in active automata learning, as well as on an intuitive and seamlessly integrated interface for learning automata characterizing real-world reactive systems. In this manuscript, we present AALpy’s core functionalities, illustrate its usage via examples, and evaluate its learning performance.

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Notes

  1. 1.

    Code, documentation, interactive examples, and a comprehensive Wiki can be found at https://github.com/DES-Lab/AALpy.

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Acknowledgments

This work has been supported by the “University SAL Labs” initiative of Silicon Austria Labs (SAL) and its Austrian partner universities for applied fundamental research for electronic based systems and by the TU Graz LEAD project “Dependable Internet of Things in Adverse Environments”.

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Authors and Affiliations

  1. Silicon Austria Labs, TU Graz - SAL DES Lab, Graz, Austria

    Edi Muškardin, Ingo Pill & Martin Tappler

  2. Institute of Software Technology, Graz University of Technology, Graz, Austria

    Edi Muškardin, Bernhard K. Aichernig, Andrea Pferscher & Martin Tappler

Authors
  1. Edi Muškardin
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  2. Bernhard K. Aichernig
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  3. Ingo Pill
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  4. Andrea Pferscher
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  5. Martin Tappler
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Corresponding author

Correspondence to Edi Muškardin .

Editor information

Editors and Affiliations

  1. Griffith University, Brisbane, QLD, Australia

    Zhe Hou

  2. University of Waterloo, Waterloo, ON, Canada

    Vijay Ganesh

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Muškardin, E., Aichernig, B.K., Pill, I., Pferscher, A., Tappler, M. (2021). AALpy: An Active Automata Learning Library. In: Hou, Z., Ganesh, V. (eds) Automated Technology for Verification and Analysis. ATVA 2021. Lecture Notes in Computer Science(), vol 12971. Springer, Cham. https://doi.org/10.1007/978-3-030-88885-5_5

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  • DOI: https://doi.org/10.1007/978-3-030-88885-5_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-88884-8

  • Online ISBN: 978-3-030-88885-5

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