A New Way about using Statistical Analysis of Worst-Case Execution Times

Abstract : In this paper, we revisit the problem of using Extreme Value Theory (EVT) in the Worst-Case Execution Time (WCET) analysis of the programs running on a single processor. Our proposed statistical WCET analysis method consists of a novel sampling mechanism tackling with some problems that hindered the application of using EVT in the context, and a statistical inference about computation of a WCET estimate of the target program. To be specific, the presented sampling mechanism takes analysis samples from the target program based around end-to-end measurements. Next, the statistical inference using EVT together with other statistical techniques, analyzes such timing traces which contain the execution time data of the program, to compute a WCET estimate with a certain predictable probability of being exceeded.
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ACM SIGBED Review, Association for Computing Machinery (ACM), 2011, 8 (3), pp.11-14. 〈10.1145/2038617.2038619〉
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https://hal.inria.fr/hal-00646572
Contributeur : Liliana Cucu <>
Soumis le : mercredi 30 novembre 2011 - 12:03:53
Dernière modification le : mardi 23 janvier 2018 - 13:26:01

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Lu Yue, Thomas Nolte, Ian Bate, Liliana Cucu-Grosjean. A New Way about using Statistical Analysis of Worst-Case Execution Times. ACM SIGBED Review, Association for Computing Machinery (ACM), 2011, 8 (3), pp.11-14. 〈10.1145/2038617.2038619〉. 〈hal-00646572〉

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