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              <p>When a failure occurs in the Linux kernel, the kernel emits an "oops", summarizing the execution context of the failure. Kernel oopses describe real Linux errors, and thus can help prioritize debugging efforts and motivate the design of tools to improve the reliability of Linux code. Nevertheless, the information is only meaningful if it is representative and can be interpreted correctly. In this paper, we study a repository of kernel oopses collected over 8 months by Red Hat. We consider the overall features of the data, the degree to which the data reflects other information about Linux, and the interpretation of features that may be relevant to reliability. We find that the data correlates well with other information about Linux, but that it suffers from duplicate and missing information. We furthermore identify some potential pitfalls in studying features such as the sources of common faults and common failing applications.</p>
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              <p>Lorsqu'une défaillance survient dans le noyau de Linux, le noyau émet un rapport de "oops" qui résume le contexte d'exécution à ce moment. Les "kernel oopses" décrivent des vrais problèmes de Linux. Ils peut aider à fixer des priorités pour les tâches de mise au point et motiver le développement d'outils permettant d'améliorer la fiabilité du code de Linux. Néanmoins, les informations des oops ne sont significatives que si elles sont représentatifs et sont interprétées correctement. Dans cet article, nous étudions les kernel oopses mémorisés pendant huit mois par Red Hat. Nous considérons les caractéristiques générales de ces rapports, la corrélation entre les rapports et d'autres informations éxtérieures, et l'interprétation des caractéristiques liée à la fiabilité de Linux. Notre étude montre principalement (i) que les kernel oopses sont corrélés aux informations extérieures, (ii) les kernel oopses souffrent de problémes de duplication et d'absence de rapports. Par ailleurs, nous avons identifiés des pièges á éviter dans l'étude des sources des fautes usuelles et dans les applications fréquement défaillantes.</p>
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