APPROXIMATION TECHNIQUES FOR TIMING ANALYSIS OF COMPLEX REAL-TIME EMBEDDED SYSTEMS

To date, many industrial embedded systems are very large, flexible, and highly configurable software systems, containing millions of lines of code and con-sisting of hundreds of tasks, many with real-time constraints, being triggered in complex, nested patterns. Furthermore, the temporal dependencies between tasks in such systems are difficult to determine analytically, and they vary the execution time and response time of tasks greatly. We refer to such systems as Complex Real-Time Embedded Systems (CRTES). To maintain, analyze and reuse such CRTES is very difficult and expensive, which, nevertheless, offers high business value in response to great concern in industry. Moreover, in such context, not only the functional behavior of sys-tems has to be assured, but also non-functional properties such as the temporal behavior, i.e., the Worst-Case Response Time (WCRT) of the adhering tasks in systems has to be known. However, due to high complexity of such systems and the nature of the problem, the exact WCRT of tasks is impossible to fin