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Work-In-Progress: Models and tools to detect Real-Time Scheduling Anomalies

Blandine Djika Frank Singhoff 1 Alain Plantec 1 Georges Kouamou
1 Lab-STICC_SHAKER - Equipe Software/HArdware and unKnown Environment inteRactions
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance : UMR6285
Abstract : This paper deals with scheduling anomalies in real-time systems. Scheduling anomalies jeopardize schedulability analysis made prior to execution. In this paper, we propose a model to specify conditions leading to scheduling anomalies. A scheduling anomaly is modeled as a set of constraints on the architecture. We use this model to detect scheduling anomalies by offline and online analysis. To validate our approach, we implemented the approach as an extension to Cheddar, a schedulability tool. We apply our approach to seven scheduling anomalies and we show that most of these anomalies can be successfully detected.
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Conference papers
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https://hal.univ-brest.fr/hal-03361920
Contributor : Frank Singhoff Connect in order to contact the contributor
Submitted on : Wednesday, November 10, 2021 - 3:28:43 PM
Last modification on : Wednesday, November 10, 2021 - 3:28:43 PM

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  • HAL Id : hal-03361920, version 1

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Blandine Djika, Frank Singhoff, Alain Plantec, Georges Kouamou. Work-In-Progress: Models and tools to detect Real-Time Scheduling Anomalies. Brief presentation at the 42nd IEEE Real-Time Systems Symposium (RTSS), Dec 2021, Dortmund, Germany. ⟨hal-03361920⟩

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