flexfringe

A Passive Automaton Learning Package

Conference paper (2017)

Authors

S.E. Verwer Cyber Security - EEMCS
C.A. Hammerschmidt University of Luxembourg
Research Group
Cyber Security (EEMCS) (TU Delft)
Software Heuristic algorithms Machine learning algorithms Tools Algorithm design and analysis Software algorithms Learning Automata
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Published Date

2017

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Cyber Security

Abstract

Finite state models, such as Mealy machines or state charts, are often used to express and specify protocol and software behavior. Consequently, these models are often used in verification, testing, and for assistance in the development and maintenance process. Reverse engineering these models from execution traces and log files, in turn, can accelerate and improve the software development and inform domain experts about the processes actually executed in a system. We present name, an open-source software tool to learn variants of finite state automata from traces using a state-of-the-art evidence-driven state-merging algorithm at its core. We embrace the need for customized models and tailored learning heuristics in different application domains by providing a flexible, extensible interface.

Files

08094471.pdf
(.pdf | 0.334 Mb)