A comparison framework for the vehicular modeling languages on enabling pre-runtime timing analysis

Handling the software complexity of modern vehicle functionalities has become very challenging due to their non-centralized nature and real-time requirements that they impose. These functionalities are usually developed as distributed real-time embedded systems composed of several nodes (Electronic Control Unit) and multiple communication protocols. Among many software development paradigms for these systems, the model-based approach excels mainly for two reasons. First, it handles the software complexity by separation of concerns through the use of models. Second, it ensures the timing predictability of these systems by adopting the timing analysis techniques proposed by the research community. They are pre-runtime timing analysis techniques that provide shreds of evidence whether all the timing requirements will be met during the execution of the system. In this thesis work, we propose a comprehensive framework that captures the timing related information needed for the modeling languages to facilitate these timing analyses. The framework is comprehensive in such a way that it identifies the generic timing properties for the nodes and network respectively. What is more, the system's timing model generated by the modeling languages requires tool support for extracting and interpreting this information. Hence, we validate the applicability of the framework by comparing two modeling languages and their respective tool-chains such as Rubus-ICE and APP4MC used in the vehicular industry