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Problem detection in real-time systems by trace analysis

Mathieu Côté and Michel Dagenais

Article (2016)

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Abstract

This paper focuses on the analysis of execution traces for real-time systems. Kernel tracing can provide useful information, without having to instrument the applications studied. However, the generated traces are often very large. The challenge is to retrieve only relevant data in order to find quickly complex or erratic real-time problems. We propose a new approach to help finding those problems. First, we provide a way to define the execution model of real-time tasks with the optional suggestions of a pattern discovery algorithm. Then, we show the resulting real-time jobs in a Comparison View, to highlight those that are problematic. Once some jobs that present irregularities are selected, different analyses are executed on the corresponding trace segments instead of the whole trace.This allows saving huge amount of time and execute more complex analyses. Our main contribution is to combine the critical path analysis with the scheduling information to detect scheduling problems. The efficiency of the proposed method is demonstrated with two test cases, where problems that were difficult to identify were found in a few minutes.

Subjects: 2700 Information technology > 2706 Software engineering
Department: Department of Computer Engineering and Software Engineering
Funders: CRSNG/NSERC, CAE, OPAL-RT, Consortium for Research and Innovation in Aerospace in Quebec (CRIAQ)
PolyPublie URL: https://publications.polymtl.ca/4831/
Journal Title: Advances in Computer Engineering (vol. 2016)
Publisher: Hindawi
DOI: 10.1155/2016/9467181
Official URL: https://doi.org/10.1155/2016/9467181
Date Deposited: 19 Jul 2021 16:02
Last Modified: 06 Apr 2024 20:13
Cite in APA 7: Côté, M., & Dagenais, M. (2016). Problem detection in real-time systems by trace analysis. Advances in Computer Engineering, 2016, 1-12. https://doi.org/10.1155/2016/9467181

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