Artifacts using automata-api version 0.3.1-ase2013-tutorial-r1

The core artifact of AutomataLib. This library contains concrete implementations for many of the automaton model interfaces defined in the API artifact, as well as abstract base classes that facilitate implementing new automaton model classes. Note that concrete algorithms (traversal, reachability analysis etc.) are part of the automata-util artifact.

This artifact provides various common utility operations for analyzing and manipulating automata and graphs, such as traversal, minimization and copying.

Infrastructure and core functionalities of LearnLib

A collection of algorithms for handling counterexamples in automata learning

A collection of basic algorithm for approximating equivalence queries

This artifact contains algorithms for incrementally constructing DFAs (prefix-closed and non-prefix-closed), Mealy machines, and Moore machines from a finite, incrementally growing set of example inputs/outputs.

A flexible, optimized version of Dana Angluin's L* algorithm

This artifact contains adapter classes for treating the Automaton objects from the BRICS library (http://www.brics.dk/automaton) as AutomataLib models.

This artifact provides the implementation of the DHC learning algorithm as described in the paper "Automata Learning with on-the-Fly Direct Hypothesis Construction" (https://doi.org/10.1007/978-3-642-34781-8_19) by Maik Merten, Falk Howar, Bernhard Steffen, and Tiziana Margaria.

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