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A New Way about using Statistical Analysis of Worst-Case Execution Times
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0002-7366-7186
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0001-6132-7945
University of York.ORCID iD: 0000-0003-2415-8219
INRIA Nancy-Grand Est, Nancy, France.
2011 (English)In: ACM SIGBED Review, ISSN 1551-3688, Vol. 8, no 3, p. 11-14Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2011. Vol. 8, no 3, p. 11-14
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-13545DOI: 10.1145/2038617.2038619OAI: oai:DiVA.org:mdh-13545DiVA, id: diva2:466088
Conference
Work-in-Progress (WiP) Session of the 23rd Euromicro Conference on Real-Time Systems (ECRTS 2011)
Available from: 2011-12-15 Created: 2011-12-15 Last updated: 2018-01-12Bibliographically approved

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Lu, YueNolte, ThomasBate, Iain

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