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In recent years, we see more and more ECUs integrating a huge number of application software components. This process mostly results from the increasing amount of so called in-house software in various fields like electric-drive, chassis and driver assistance systems. The software development for these systems is partially moved from the supplier to the car manufacturers. Another important trend is the introduction of new network architectures intending to meet the growing communication requirements. For such ECUs the software integration scenarios become more complicated, as more quality of service requirements with regards to timing, safety and security need to be considered [2]. Multi-core microcontrollers offer even more potential variants for integration scenarios. Understanding the interaction between the different software components, not only from a functional, but also from a timing view, is a key success factor for modern electronic systems [6,7,8,9].

With the increasing complexity of electronic vehicle systems, one particular “gap” between function development and ECU integration becomes more and more apparent, and critical; albeit not new. The core of the problem is: as more functions are integrated and share the same E/E resources, they increasingly mutually influence and disturb each other in terms of memory, peripherals, and also timing and performance. This has two consequences: The amount of timing-related errors increases (because of the disturbance) and it becomes more difficult to find root causes of timing errors (because of the mutual influences). This calls for more systematic methods to deal with timing requirements in general and their transformation from function timing requirements to software architecture timing requirements in particular.

Integration scenarios for ECU software become more complicated, as more constraints with regards to timing, safety and security need to be considered. Multi-core microcontrollers offer even more hardware potential for integration scenarios. To tackle the complexity, more and more model based approaches are used. Understanding the interaction between the different software components, not only from a functional but also from a timing view, is a key success factor for high integration scenarios. In particular for multi-core systems, an amazing amount of timing data can be generated. Usually a multi-core system handles more software functionality than a single-core system. Furthermore, there may be timing interference on the multicore systems, due to the shared usage of buses, memory banks or other hardware resources.