The control system of many complex mechatronic products requires for each task
the Worst Case Execution Time (WCET), which is needed for the scheduler's
admission tests and subsequently limits a task's execution time during
operation. If a  task exceeds the WCET, this situation is detected and either a
handler is invoked or control is transferred to a human operator. Such control
systems usually support preemptive multitasking, and if  an object-oriented
programming language (e.g., Java, C++, Oberon) is used, then the system may also
provide dynamic loading and unloading of software components (modules).
Only modern, state-of-the art microprocessors can provide the necessary compute
cycles, but  this combination of features (preemption, dynamic un/loading of
modules, advanced processors) creates unique challenges when estimating the
WCET. Preemption makes it difficult to take the state of the caches and
pipelines into account when determining the WCET, yet for modern processors, a
WCET based on worst-case assumptions about caches and pipelines is too large to
be useful, especially for big and complex real-time products. Since modules can
be loaded and unloaded, each task must be analyzed in isolation, without
explicit reference to other tasks that may execute concurrently.

To obtain a realistic estimate of a task's execution time, we use static
analysis of the source code combined with information about the task's runtime
behavior. Runtime information is gathered by the performance monitor that is
included in the processor's hardware implementation. Our predictor is able to
compute a good estimation of the WCET even for complex  tasks that contain a lot
of dynamic cache usage, and its requirements are met by today's performance
monitoring hardware. The paper includes data to evaluate the effectiveness of
the proposed technique for a number of robotics control kernels that are
written in an object-oriented programming language and execute  on a PowerPC
604e-based system.