Team MExICo

Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Other Grants and Activities

Section: Software


libalf : the Automata Learning Framework

Participant : Benedikt Bollig [ correspondant ] .

libalf is a comprehensive, open-source library for learning finite-state automata covering various well-known learning techniques (such as, Angluin s L* , Biermann, and RPNI, as well as a novel learning algorithm for NFA. libalf is highly flexible and allows for facilely interchanging learning algorithms and combining domain-specific features in a plug-and-play fashion. Its modular design and its implementation in C++ make it a flexible platform for adding and engineering further, efficient learning algorithms for new target models (e.g., Büchi automata).

Details on libalf can be found at

Mole: an unfolder for Petri Nets

Participant : Stefan Schwoon [ correspondant ] .

Mole computes, given a safe Petri net, a finite prefix of its unfolding. It is designed to be compatible with other tools, such as PEP and the Model-Checking Kit, which are using the resulting unfolding for reachability checking and other analyses. The tool Mole arose out of earlier work on Petri nets. In the context of MExiCo, we are extending it to handle contextual Petri nets. A preliminary (but inefficient) implementation has been achieved, which we intend to improve to obtain a viable, efficient tool.

Details on Mole can be found at


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