Raphaël Beamonte et Michel Dagenais
Article de revue (2016)
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Abstract
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.
Sujet(s): |
2700 Technologie de l'information > 2700 Technologie de l'information 2700 Technologie de l'information > 2719 Architecture d'ordinateur et conception |
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Département: | Département de génie informatique et génie logiciel |
Organismes subventionnaires: | CRSNG/NSERC, CAE, Opal-RT, Consortium de recherche et d'innovation en aérospatiale au Québec |
URL de PolyPublie: | https://publications.polymtl.ca/3065/ |
Titre de la revue: | Scientific Programming (vol. 2016) |
Maison d'édition: | Hindawi |
DOI: | 10.1155/2016/9792462 |
URL officielle: | https://doi.org/10.1155/2016/9792462 |
Date du dépôt: | 04 mai 2018 16:10 |
Dernière modification: | 27 sept. 2024 11:02 |
Citer en APA 7: | Beamonte, R., & Dagenais, M. (2016). Detection of common problems in real-Time and multicore systems using model-based constraints. Scientific Programming, 2016, 1-18. https://doi.org/10.1155/2016/9792462 |
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