Group: LearnLib

This artifact provides the implementations of various learning algorithms for systems of procedural automata such as the ones described in the papers "Compositional learning of mutually recursive procedural systems (https://doi.org/10.1007/s10009-021-00634-y) and "From Languages to Behaviors and Back" (https://doi.org/10.1007/978-3-031-15629-8_11) by Markus Frohme and Bernhard Steffen.

A simple, straightforward implementation of Dana Angluin's L* algorithm

This artifact provides the implementation of the NL* learning algorithm as described in the paper "Angluin-Style Learning of NFA" (http://ijcai.org/Proceedings/09/Papers/170.pdf) by Benedikt Bollig, Peter Habermehl, Carsten Kern, and Martin Leucker.

This artifact provides the implementation of the VPA adaption of the TTT learning algorithm as presented in the PhD thesis "Foundations of Active Automata Learning: An Algorithmic Perspective" (https://dx.doi.org/10.17877/DE290R-16359) by Malte Isberner.

The TTT Algorithm (visibly push-down automata variant)

A collection of property oracles

This artifact provides the implementation of (a blue-fringe version of) the "regular positive negative inference" (RPNI) learning algorithm as presented in the paper "Inferring regular languages in polynomial update time" (https://dx.doi.org/10.1142/9789812797902_0004) by Jose Oncina and Pedro García using the "minimum description length" (MDL) heuristic. More details on this algorithm can be found in the book "Grammatical Inference" ...

This artifact provides the implementation of the "onward subsequential transducer inference algorithm" (OSTIA) learning algorithm as presented in the paper "Learning Subsequential Transducers for Pattern Recognition Interpretation Tasks" (https://doi.org/10.1109/34.211465) by Jose Oncina, Pedro García, and Enrique Vidal.

This artifact provides the implementation of (a blue-fringe version of) the "regular positive negative inference" (RPNI) learning algorithm as presented in the paper "Inferring regular languages in polynomial update time" (https://dx.doi.org/10.1142/9789812797902_0004) by Jose Oncina and Pedro García using the "evidence-driven state merging" (EDSM) heuristic. More details on this algorithm can be found in the book "Grammatical Inference" ...

This artifact provides the implementation of the ADT learning algorithm as described in the Master thesis "Active Automata Learning with Adaptive Distinguishing Sequences" (http://arxiv.org/abs/1902.01139) by Markus Frohme.

A collection of examples of how to use LearnLib

Parent module for equivalence testing algorithms shipped with LearnLib

A framework for active automata learning and experimentation

A utility parent, that defines certain plugin executions for the build process. May be used to define dependencies on the "build-tools" artifact without introducing cyclic dependencies with the general parent.

Parent module for (active) automata learning algorithms shipped with LearnLib

Configs and other resources required for building LearnLib

Parent module for data structures shared across multiple modules of LearnLib

Parent module for oracles and oracle-related modules

Parent module for test drivers

Parent module for automata learning algorithms shipped with LearnLib