PUB: Path Upper-Bounding for Measurement-Based Probabilistic Timing Analysis

Measurement-Based Probabilistic Timing Analysis (MBPTA) responds to the challenge of analysing the timing behaviour of real-time software running on hardware deploying high-performance features (e.g., data caches). MBPTA provides a WCET estimate that upper-bounds the execution time of the set of paths exercised with the data input vectors provided by the user. However, in several scenarios, the user is unaware of the input vector leading to the worst-case path. In this paper we present PUB, a new method that makes the WCET estimates obtained with MBPTA a trustworthy upper-bound of the probabilistic execution time of all paths in the program, even when the user-provided input vectors do not exercise the worst-case path. This significantly reduces the requirements imposed on the user to apply MBPTA. For Malardarlen and EEMBC respectively, PUB provides WCET estimates 5% and 11% higher than the WCET estimates computed with MBPTA.