Features

Active Automata Learning Algorithms

Be sure to also check out the blazing performance of LearnLib’s learning algorithm implementations.

Equivalence Test Approximation Algorithms

  • Complete, depth-bounded exploration
  • Random words
  • Random walk
  • W-method
  • Wp-method

Filters

  • Query cache
  • Reuse filter

Framework

  • Generic, extensible design
  • Logging subsystem

Feature Matrix

The following table lists where the open-source LearnLib features differ from those of the former, closed-source version. Note that the publicly available version of the old LearnLib only contains a subset of all implemented features.

Feature Open-source LearnLib Old LearnLib (public release) Old LearnLib (internal)
TTT algorithm
Wp-method
Random walk
Reuse filter
Register Automata learning
Generic design
Graphical modeling tool (LearnLib studio)

Contact us if you are interested in a feature that currently is available in the internal version of the old LearnLib only. Maybe you are even interested in porting this feature to the new, open-source LearnLib. Your contribution would greatly be appreciated.