Artifacts using automata-api version 0.7.0

Utilities for simulating SULs

Caches to avoid posing duplicate membership queries

Generic automata serialization core

Data- and utility classes for Discrimination Trees

Filters for collecting statistical data

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.

Support for posing membership queries in parallel

Data- and utility classes for Prefix-Tree-Acceptors

This artifact provides the implementation of the L* learning algorithm described in the paper "Learning Regular Sets from Queries and Counterexamples" (https://doi.org/10.1016/0890-5401(87)90052-6) by Dana Angluin including variations and optimizations thereof such as the versions based on "On the Learnability of Infinitary Regular Sets" (https://doi.org/10.1006/inco.1995.1070) by Oded Maler and Amir Pnueli or "Inference of finite automata using homing sequences" ...

A collection of utility methods to parse LearnLib specific settings.