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.
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 - 19th International Symposium, ATVA 2021 |
| Subtitle of host publication | , Gold Coast, Australia, October 18-22, 2021, Proceedings |
| Publication status | Accepted/In press - 18 Oct 2021 |