Artifacts using automata-api version 0.5.2

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.

Example learning setups to be used for integration testing

Infrastructure and core functionalities of LearnLib

A collection of algorithms for handling counterexamples in automata learning

Generic automata serialization core

A collection of basic algorithm for approximating equivalence queries

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

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 learning algorithm, which distinguishes hypothesis states using a discrimination tree.