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A listing of some learning and testing tools:

  • LearnLib: a free, open-source (LGPLv3) Java library for active automata learning. A simple getting-started project can be found here.
  • LibAlf: a comprehensive, open-source library for learning finite-state automata covering various well-known learning techniques (such as Angluin's L*, Biermann's learning approach, and RPNI), as well as novel learning algorithms (e.g. for NFA and visibly one-counter automata).
  • RALib: a library for active learning algorithms for register automata. RALib is licensed under the Apache License, Version 2.0. RALib is developed as an extension to LearnLib.
  • Tomte: a tool for learning register automata. The tool uses counterexample guided abstraction refinement to automatically construct abstractions, and uses a Mealy machine learner (such as LearnLib) as a back-end.
  • (J)Torx: JTorX [Bel10] is an update of the model-based testing tool TorX [TB03]. TorX is a model-based testing tool that uses labeled transition systems to derive and execute tests (execution traces) based on ioco [Tre08], a theory for defining when an implementation of a given specification is correct. Using on-line testing, JTorX can easily generate and execute tests consisting of more than 1 000 000 test events. JTorX is easier to deploy and uses a more advanced version of ioco. It contains a graphical user interface for easy configuration, a simulator for guided evaluation of a test trace, interfaces for communication with an SUT, and state-of-the-art testing algorithms.
  • TorXakis: a tool for model based testing.