Sep 21, 2020 · In this article, we show how we can boost the performance of model learning techniques by extracting the constraints on input and output ...

Nov 13, 2020 · Model learning (a.k.a. active automata learning) is a highly effective technique for obtaining black-box finite state models of software ...

In this article, we show how we can boost the performance of model learning techniques by extracting the constraints on input and output parameters from a run, ...

Generating models of infinite-state communication protocols using regular inference with abstraction · Computer Science. Formal methods in system design · 2014.

Sep 21, 2020 · In this article, we show how we can boost the performance of model learning techniques by extracting the constraints on input and output ...

Model learning (a.k.a. active automata learning) is a highly effective technique for obtaining black-box finite state models of software components.

Aarts, F., Heidarian, F., Kuppens, H., Olsen, P., Vaandrager, F.: Automata learning through counterexample guided abstraction refinement.

Model learning (a.k.a. active automata learning) is a highly effective technique for obtaining black-box finite state models of software components.

Model learning (a.k.a. active automata learning) is a highly effective technique for obtaining black-box finite state models of software components.

Grey-Box Learning of Register Automata ; Fulltext: 226661.pdf ; Size: 504.4Kb ; Format: PDF ; Description: Publisher's version.