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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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https://hal.inria.fr/hal-00646572
Contributor : Liliana Cucu-Grosjean <>
Submitted on : Wednesday, November 30, 2011 - 12:03:53 PM
Last modification on : Friday, February 26, 2021 - 3:28:07 PM

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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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