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

TL;DR

This paper introduces SLNET, the largest open-source corpus of third-party Simulink models, enabling large-scale empirical studies and advancing research in model-based design for safety-critical systems.

Contribution

SLNET is a large, automatically constructed, and redistributable corpus of third-party Simulink models with detailed metadata, surpassing previous collections in size and accessibility.

Findings

SLNET is 8 times larger than previous Simulink model collections.

SLNET includes detailed metadata for each model.

SLNET is freely available under permissive licenses.

Abstract

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.