eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Open Access Series in Informatics
2190-6807
2009-11-26
1
11
10.4230/OASIcs.WCET.2009.2291
article
Statistical-Based WCET Estimation and Validation
Hansen, Jeffery
Hissam, Scott
Moreno, Gabriel A.
In this paper we present a measurement-based approach that produces both a WCET (Worst Case Execution Time) estimate, and a prediction of the probability that a future execution time will exceed our estimate. Our statistical-based approach uses extreme value theory to build a model of the tail behavior of the measured execution time value. We validate our approach using an industrial data set comprised of over 150 sampled components and nearly 200 million sample execution times. Each trace is divided into two segments, with one used to make the WCET estimate, and the second used check our prediction of the fraction of future execution time samples that exceed our WCET estimate. We show that compared to WCET estimates derived from the worst-case observed time, our WCET estimates significantly improve the ability to predict the probability that our WCET estimate is exceeded.
https://drops.dagstuhl.de/storage/01oasics/oasics-vol010-wcet2009/OASIcs.WCET.2009.2291/OASIcs.WCET.2009.2291.pdf
WCET analysis
measurement-based
extreme value theory
EVT
Gumbel