Learning Register Automata with Fresh Value Generation

F. Aarts, P. Fiterau-Brostean, H. Kuppens, and F.W. Vaandrager. Learning Register Automata with Fresh Value Generation. In M. Leucker, C. Rueda and F.D. Valencia, editors. Proceedings 12th International Colloquium on Theoretical Aspects of Computing (ICTAC 2015), Cali, Colombia, October 29-31, 2015. LNCS 9399, pp. 1-19, Springer Verlag, 2015. DOI: 10.1007/978-3-319-25150-9 11.

Abstract

We present a new algorithm for active learning of register automata. Our algorithm uses counterexample-guided abstraction refinement to automatically construct a component which maps (in a history dependent manner) the large set of actions of an implementation into a small set of actions that can be handled by a Mealy machine learner. The class of register automata that is handled by our algorithm extends previous definitions since it allows for the generation of fresh output values. This feature is crucial in many real-world systems (e.g. servers that generate identifiers, passwords or sequence numbers). We have implemented our new algorithm in a tool called Tomte.

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Slides (pdf) presenting in particular the determinizer