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Weakly hard real-time systems can, to some degree, tolerate deadline misses,but their schedulability still needs to be analyzed to ensure their quality ofservice. Such analysis usually occurs at early design stages to provideimplementation guidelines to engineers so that they can make better designdecisions. Estimating worst-case execution times (WCET) is a key input toschedulability analysis. However, early on during system design, estimatingWCET values is challenging and engineers usually determine them as plausibleranges based on their domain knowledge. Our approach aims at findingrestricted, safe WCET sub-ranges given a set of ranges initially estimated byexperts in the context of weakly hard real-time systems. To this end, weleverage (1) multi-objective search aiming at maximizing the violation ofweakly hard constraints in order to find worst-case scheduling scenarios and(2) polynomial logistic regression to infer safe WCET ranges with aprobabilistic interpretation. We evaluated our approach by applying it to anindustrial system in the satellite domain and several realistic syntheticsystems. The results indicate that our approach significantly outperforms abaseline relying on random search without learning, and estimates safe WCETranges with a high degree of confidence in practical time (< 23h).

Probabilistic Safe WCET Estimation for Weakly Hard Real-Time Systems at Design Stages