Identification of Simulink model antipattern instances using model clone detection

One challenge facing the Model-Driven Engineering community is the need for model quality assurance. Specifically, there should be better facilities for analyzing models automatically. One measure of quality is the presence or absence of good and bad properties, such as patterns and antipatterns, respectively. We elaborate on and validate our earlier idea of detecting patterns in model-based systems using model clone detection by devising a Simulink antipattern instance detector. We chose Simulink because it is prevalent in industry, has mature model clone detection techniques, and interests our industrial partners. We demonstrate our technique using near-miss cross-clone detection to find instances of Simulink antipatterns derived from the literature in four sets of public Simulink projects. We present our detection results, highlight interesting examples, and discuss potential improvements to our approach. We hope this work provides a first step in helping practitioners improve Simulink model quality and further research in the area.