SLNET: A Redistributable Corpus of 3rd-party Simulink Models
| Autor: | Shrestha, Sohil Lal, Chowdhury, Shafiul Azam, Csallner, Christoph |
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| Rok vydání: | 2022 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1145/3524842.3528001 |
| Popis: | 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 all of its collection and analysis tools. Comment: Published in Mining Software Repositories 2022 - Data and Tool Showcase Track |
| Databáze: | arXiv |
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