The Need for a Better Way to Predict Performance of Real-Time Embedded Systems
Traditionally, embedded systems engineering practice has been manual, paper intensive, error prone, and resistant to change. Specification, design, development, and validation of systems has been lacking in a precise capture of the system architecture and its analysis early in and throughout the development process. The result: a lack of insight into critical system characteristics—those nonfunctional attributes such as performance (e.g., throughput or quality of service), safety, reliability, time criticality, security, and fault tolerance. System integration becomes high risk, and system evolution (life-cycle support) becomes expensive and results in rapidly outdated components.
Figure 1: Current software development is
manual, paper intensive, error prone, and resistant to change
By contrast, improved embedded systems engineering practice would be architecture-based and model-driven. Well-defined software system architecture provides a framework to which system components are designed and integrated. System models that precisely capture this architecture provide the basis for predictable embedded system engineering through repeated analysis early in and throughout the development life cycle.
The SAE AADL is an industry standard notation that was explicitly designed to support such model-based embedded system engineering.