Algorithms for inferring register automata: A comparison of existing approaches

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.