AALpy: An Active Automata Learning Library

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

doi:10.1007/978-3-030-88885-5_5

AALpy: An Active Automata Learning Library

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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.

Original language	English
Title of host publication	Automated Technology for Verification and Analysis - ATVA 2021
Editors	Zhe Hou, Vijay Ganesh
Place of Publication	Cham
Publisher	Springer
Pages	67-73
Number of pages	7
ISBN (Electronic)	978-3-030-88885-5
ISBN (Print)	978-3-030-88884-8
DOIs	https://doi.org/10.1007/978-3-030-88885-5_5
Publication status	Published - 2021
Event	19th International Symposium on Automated Technology for Verification and Analysis : ATVA 2021 - Virtuell, Australia Duration: 18 Oct 2021 → 22 Oct 2021

Publication series

Name	Lecture Notes in Computer Science
Volume	12971
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th International Symposium on Automated Technology for Verification and Analysis
Abbreviated title	ATVA 2021
Country/Territory	Australia
City	Virtuell
Period	18/10/21 → 22/10/21

Keywords

Active automata learning
Model inference
Python

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-88885-5_5

Cite this

AALpy: An Active Automata Learning Library. / Muskardin, Edi; Aichernig, Bernhard; Pill, Ingo et al.
Automated Technology for Verification and Analysis - ATVA 2021. ed. / Zhe Hou; Vijay Ganesh. Cham: Springer, 2021. p. 67-73 (Lecture Notes in Computer Science; Vol. 12971 ).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Muskardin, E, Aichernig, B, Pill, I, Pferscher, A & Tappler, M 2021, AALpy: An Active Automata Learning Library. in Z Hou & V Ganesh (eds), Automated Technology for Verification and Analysis - ATVA 2021. Lecture Notes in Computer Science, vol. 12971 , Springer, Cham, pp. 67-73, 19th International Symposium on Automated Technology for Verification and Analysis , Virtuell, Australia, 18/10/21. https://doi.org/10.1007/978-3-030-88885-5_5

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AALpy: An Active Automata Learning Library

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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Dependable Internet of Things

Cite this

AALpy: An Active Automata Learning Library

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Projects

Dependable Internet of Things

Cite this