Extracting, specifying and predicting software system properties in component based real-time embedded software development

Bosch has established Component Based Software Development (CBSD) for automotive systems, which are resource constrained real-time embedded systems such as engine control systems. Classical CBSD approaches enable effective software reuse mainly in functional aspects by managing complexity with abstraction and encapsulation. However, to fully exploit the advantages of CBSD for real-time embedded systems, non-functional system properties such as timing and memory usage need to be addressed by the underlying component model. It is important that non-functional properties have a certain degree of precision to ensure hardware dimensioning and cost optimization for such systems. Static analysis methods used to extract or analyze nonfunctional properties (e.g., worst case execution time) in most cases introduce overestimation which is a hindrance for accurate prediction of non-functional properties. Therefore, accurate prediction of system properties requires specifying semantic context information such as modes in the component model to reduce overestimation. This paper describes how we extend the Bosch software component model to specify non-functional component properties with modes information. We demonstrate how mode dependent timing behavior is automatically extracted from the software, specified in the component specification and used for analysis and prediction in real-time embedded systems. This paper shows that semantic context information such as modes enhances performance analysis and prediction by ruling out infeasible worst-case situations that lead to overly conservative performance predictions.