SLNET: A Redistributable Corpus of 3rd-party Simulink Models

Published in MSR (CORE A , Acceptance rate: 74% (high acceptance rate has to do with the high-quality submission to the datashowcase track)) , 2022

Recommended citation: Sohil Lal Shrestha, Shafiul Azam Chowdhury and Christoph Csallner. "SLNET: A Redistributable Corpus of 3rd-party Simulink Models. IEEE/ACM 19th International Conference on Mining Software Repositories (MSR). 2022

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MATLAB/Simulink is widely used for model-based design. Engineers create Simulink models and compile them to embedded code, often to control safety-critical cyber-physical systems in automotive, aerospace, and healthcare applications. Despite Simulink’s importance, there are few large-scale empirical Simulink studies, perhaps because there is no large readily available corpus of third-party open-source Simulink models. To enable empirical Simulink studies, this paper introduces SLNET, the largest corpus of freely available third-party Simulink models. SLNET has several advantages over earlier collections. Specifically, SLNET is 8 times larger than the largest previous corpus of Simulink models, includes fine-grained metadata, is constructed automatically, is self-contained, and allows redistribution. SLNET is available under permissive open-source licenses and contains its collection and analysis tools.