Abstract
In recent years, two different approaches for learning register automata have been developed: as part of the LearnLib tool algorithms have been implemented that are based on the Nerode congruence for register automata, whereas the Tomte tool implements algorithms that use counterexample-guided abstraction refinement to automatically construct appropriate mappers. In this paper, we compare the LearnLib and Tomte approaches on a newly defined set of benchmarks and highlight their differences and respective strengths.
The work of Aarts, Kuppens and Vaandrager was supported by STW project 11763 ITALIA: Integrating Testing And Learning of Interface Automata.
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Aarts, F., Howar, F., Kuppens, H., Vaandrager, F. (2014). Algorithms for Inferring Register Automata. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation. Technologies for Mastering Change. ISoLA 2014. Lecture Notes in Computer Science, vol 8802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45234-9_15
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