AALpy: An Active Automata Learning Library

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

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.