Benchmarks for Automata Learning and Conformance Testing

D. Neider, R. Smetsers, F.W. Vaandrager, and H. Kuppens. Benchmarks for Automata Learning and Conformance Testing. In T. Margaria, K.G. Larsen and S. Graf, editors. Models, Mindsets, Meta: The What, the How, and the Why Not? LNCS 11200, pp 390-416, Springer, Cham, 2019.


We describe a large collection of benchmarks, publicly available through the wiki, of different types of state machine models: DFAs, Moore machines, Mealy machines, interface automata and register automata. Our repository includes both randomly generated state machines and models of real protocols and embedded software/hardware systems. These benchmarks will allow researchers to evaluate the performance of new algorithms and tools for active automata learning and conformance testing.

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