AALpy: An Active Automata Learning Library

Edi Muskardin, Bernhard Aichernig, Ingo Pill, Andrea Pferscher, Martin Tappler

    Publikation: Konferenzband/Beitrag in Buch/BerichtKonferenzartikelBegutachtung

    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.
    OriginalspracheEnglisch
    TitelAutomated Technology for Verification and Analysis - 19th International Symposium, ATVA 2021
    Untertitel, Gold Coast, Australia, October 18-22, 2021, Proceedings
    PublikationsstatusAngenommen/Im Druck - 18 Okt. 2021

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