MATLAB Simulink is the most widely used industrial tool for developing complex embedded systems in the automotive sector. The resulting Simulink models often consist of more than ten thousand blocks and a large number of hierarchy levels. To ensure the quality of such models, automated static analyses and slicing are necessary to cope with this complexity. In particular, static analyses are required that operate directly on the models. In this article, we present an approach for slicing Simulink Models using dependence graphs and demonstrate its efficiency using case studies from the automotive and avionics domain. With slicing, the complexity of a model can be reduced for a given point of interest by removing unrelated model elements, thus paving the way for subsequent static quality assurance methods.
['Robert Reicherdt', 'Sabine Glesner']
Slicing MATLAB simulink models