Extending AALpy with Passive Learning: A Generalized State-Merging Approach

• URL: http://arxiv.org/abs/2506.06333v2
• Date: Thu, 12 Jun 2025 07:46:40 GMT
• Title: Extending AALpy with Passive Learning: A Generalized State-Merging Approach
• Authors: Benjamin von Berg, Bernhard K. Aichernig,
• Abstract summary: AALpy is a well-established open-source automata learning library written in Python.<n>We describe how to define and execute state-merging algorithms using AALpy.
• Score: 1.179136493190695
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: AALpy is a well-established open-source automata learning library written in Python with a focus on active learning of systems with IO behavior. It provides a wide range of state-of-the-art algorithms for different automaton types ranging from fully deterministic to probabilistic automata. In this work, we present the recent addition of a generalized implementation of an important method from the domain of passive automata learning: state-merging in the red-blue framework. Using a common internal representation for different automaton types allows for a general and highly configurable implementation of the red-blue framework. We describe how to define and execute state-merging algorithms using AALpy, which reduces the implementation effort for state-merging algorithms mainly to the definition of compatibility criteria and scoring. This aids the implementation of both existing and novel algorithms. In particular, defining some existing state-merging algorithms from the literature with AALpy only takes a few lines of code.

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