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On the Criticality of Probabilistic Worst-Case Execution Time Models

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Dependable Software Engineering. Theories, Tools, and Applications (SETTA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10606))

Abstract

Probabilistic approaches to timing analysis derive probability distributions to upper bound task execution time. The main purpose of probability distributions instead of deterministic bounds, is to have more flexible and less pessimistic worst-case models. However, in order to guarantee safe probabilistic worst-case models, every possible execution condition needs to be taken into account.

In this work, we propose probabilistic representations which is able to model every task and system execution conditions, included the worst-cases. Combining probabilities and multiple conditions offers a flexible and accurate representation that can be applied with mixed-critical task models and fault effect characterizations on task executions. A case study with single- and multi-core real-time systems is provided to illustrate the completeness and versatility of the representation framework we provide.

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Notes

  1. 1.

    In the following, calligraphic letters are used to represent distributions while non-calligraphic letters are for scalars or deterministic values.

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Author information

Authors and Affiliations

  1. ONERA, Toulouse, France

    Luca Santinelli

  2. Missouri University of Science and Technology, Rolla, USA

    Zhishan Guo

Authors
  1. Luca Santinelli
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  2. Zhishan Guo
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Corresponding author

Correspondence to Luca Santinelli .

Editor information

Editors and Affiliations

  1. Aalborg University, Aalborg, Denmark

    Kim Guldstrand Larsen

  2. University of Pennsylvania, Philadelphia, Pennsylvania, USA

    Oleg Sokolsky

  3. National University of Defense Technology, Changsha, China

    Ji Wang

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Santinelli, L., Guo, Z. (2017). On the Criticality of Probabilistic Worst-Case Execution Time Models. In: Larsen, K., Sokolsky, O., Wang, J. (eds) Dependable Software Engineering. Theories, Tools, and Applications. SETTA 2017. Lecture Notes in Computer Science(), vol 10606. Springer, Cham. https://doi.org/10.1007/978-3-319-69483-2_4

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  • DOI: https://doi.org/10.1007/978-3-319-69483-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69482-5

  • Online ISBN: 978-3-319-69483-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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