LearnLib: 10 years later Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.1007/978-3-031-98685-7_7
· OA: W4412544495
In 2015, LearnLib, the open-source framework for active automata learning, received the prestigious CAV artifact award. This paper presents the advancements made since then, highlighting significant additions to LearnLib, including state-of-the-art algorithms, novel learning paradigms, and increasingly expressive models. Our efforts to mature and maintain LearnLib have resulted in its widespread use among researchers and practitioners alike. A key factor in its success is the achieved compositionality which allows users to effortlessly construct thousands of customized learning processes tailored to their specific requirements. This paper illustrates these features through the development of a learning process for the life-long learning of procedural systems. This development can be easily replicated and modified using the latest public release of LearnLib.
