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Source code and data relevant for the paper 'Combining Model Learning and Model Checking to Analyze TCP Implementations'

DANS Data Station Physical and Technical Sciencesvia DANS Data Stations (via DataCite) · updated 7 December 2023

What's in it

The dataset contains source code and data relevant for the paper "Combining Model Learning and Model Checking to Analyze TCP Implementations".Paper url: https://link.springer.com/chapter/10.1007/978-3-319-41540-6_25PDF url: http://www.sws.cs.ru.nl/publications/papers/fvaan/FJV16/main.pdfRamon Janssen's Master's thesis url: http://www.ru.nl/publish/pages/769526/z_thesis_ramon_janssen.pdfIn this work, we use automata learning with abstraction to infer models of 3 TCP client and server implementations (Windows, Linux, FreeBSD). We then verify properties on these models using the NuSMV model checker. The dataset comprises the software components of our experimental setup apart from the actual implementations, some useful scripts and the learned models and associated experimental logs.In more concrete terms, the dataset contains:- the learner (setup) implementation - Java code for the setup built around LearnLib to perform learning with abstraction over sockets. Abstraction is provided by a mapper, described in a mapper language described in the Master's thesis.- the mapper library - Java code for loading mappers written in the mapper language and executing them in both directions …

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