State-Based Real-Time Analysis for Function Networks and Marte

Abstract

State-based real-time scheduling analyses offer a high accuracy especially for chains of functions. In this work we extend our state-based approach to also support complex activation behavior of the functions. Additionally, we use standard modeling techniques and well defined formalisms to foster the applicability and usability of our scheduling analysis. In our approach we use M ARTE to model the underlying architecture of a system consisting of embedded control units and bus systems. For timing requirements we use the requirement specification language RSL. In order to model complex activation patterns and internal states, we use an extended task network formalism called function networks. Our approach is evaluated with an industrial driver assistance system case study.