Predicting Worst-Case Execution Time Trends in Long-Lived Real-Time Systems

Dai, Xiaotian orcid.org/0000-0002-6669-5234 and Burns, Alan orcid.org/0000-0001-5621-8816 (2017) Predicting Worst-Case Execution Time Trends in Long-Lived Real-Time Systems. In: Bader, Markus and Blieberger, Johann, (eds.) Reliable Software Technologies - Ada-Europe 2017 - 22nd Ada-Europe International Conference on Reliable Software Technologies, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . , pp. 87-101.

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Copyright, Publisher and Additional Information: © Springer International Publishing AG 2017. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details
Keywords: Extreme value theory,Linear regression,Support vector regression,Trend prediction,Worst-case execution time,Theoretical Computer Science,Computer Science
Dates:
  • Published: 30 May 2017
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
Depositing User: Pure (York)
Date Deposited: 20 Jul 2018 08:50
Last Modified: 12 Sep 2021 10:31
Published Version: https://doi.org/10.1007/978-3-319-60588-3_6
Status: Published
Series Name: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Refereed: No
Identification Number: https://doi.org/10.1007/978-3-319-60588-3_6
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