A Methodology to Efficiently Compare Operating System Stability

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Abstract

Despite decades of advances in software engineering, operating systems (OSes) are still plagued by crashes due to software faults, calling for techniques to improve OS stability when faults occur. Evaluating such techniques requires a way to compare the stability of different OSes that is both representative of real faults and scales to the large code bases of modern OSes and a large (and statistically sound) number of experiments.

In this paper, we propose a widely applicable methodology meeting all such requirements. Our methodology relies on a novel fault injection strategy based on a combination of static and run-time instrumentation, which yields representative software faults while drastically reducing the instrumentation time and thus greatly enhancing scalability. To guarantee unbiased and comparable results, finally, our methodology relies on the use of pre- and posttests to isolate the direct impact of faults from the stability of the OS itself. We demonstrate our methodology by comparing the stability of Linux and MINIX 3, saving a total of 115 computer-days for the 12,000 Linux fault injection runs compared to the traditional approach of re-instrumenting for every run.
Original languageEnglish
Title of host publicationProceedings of the 16th IEEE International Symposium on High Assurance Systems Engineering
PublisherIEEE CS
Pages93-100
ISBN (Electronic)978-1-4799-8111-3
DOIs
Publication statusPublished - 2015
Event16th IEEE International Symposium on High Assurance Systems Engineering (HASE) -
Duration: 8 Jan 201510 Jan 2015

Conference

Conference16th IEEE International Symposium on High Assurance Systems Engineering (HASE)
Period8/01/1510/01/15

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  • Cite this

    van der Kouwe, E., Giuffrida, C., Ghitulete, R., & Tanenbaum, A. S. (2015). A Methodology to Efficiently Compare Operating System Stability. In Proceedings of the 16th IEEE International Symposium on High Assurance Systems Engineering (pp. 93-100). IEEE CS. https://doi.org/10.1109/HASE.2015.22