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Detection of common problems in real-Time and multicore systems using model-based constraints

Raphaël Beamonte and Michel R. Dagenais

Article (2016)

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Cite this document: Beamonte, R. & Dagenais, M. R. (2016). Detection of common problems in real-Time and multicore systems using model-based constraints. Scientific Programming, 2016, p. 1-18. doi:10.1155/2016/9792462
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Multicore systems are complex in that multiple processes are running concurrently and can interfere with each other. Real-time systems add on top of that time constraints, making results invalid as soon as a deadline has been missed. Tracing is often the most reliable and accurate tool available to study and understand those systems. However, tracing requires that users understand the kernel events and their meaning. It is therefore not very accessible. Using modeling to generate source code or represent applications’ workflow is handy for developers and has emerged as part of the model-driven development methodology. In this paper, we propose a new approach to system analysis using model-based constraints, on top of userspace and kernel traces. We introduce the constraints representation and how traces can be used to follow the application’s workflow and check the constraints we set on the model. We then present a number of common problems that we encountered in real-time and multicore systems and describe how our model-based constraints could have helped to save time by automatically identifying the unwanted behavior.

Open Access document in PolyPublie
Subjects: 2700 Technologie de l'information > 2700 Technologie de l'information
2700 Technologie de l'information > 2719 Architecture d'ordinateur et conception
Department: Département de génie informatique et génie logiciel
Research Center: Non applicable
Funders: CRSNG/NSERC, CAE, Opal-RT, Consortium de recherche et d'innovation en aérospatiale au Québec
Date Deposited: 04 May 2018 16:10
Last Modified: 08 Apr 2021 10:43
PolyPublie URL: https://publications.polymtl.ca/3065/
Document issued by the official publisher
Journal Title: Scientific Programming (vol. 2016)
Publisher: Hindawi
Official URL: https://doi.org/10.1155/2016/9792462


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