A Statistical Approach to Predict Operating System Failures Based on Multiple Failures Association
Resumo
Empirical studies have shown robust evidence of OS failure patterns characterized by multiple combinations of failure events composed of the same or different failure types. In this paper, we present a statistical approach to predict OS failures based on multiple failures association. Once we identify systematic failure associations in field data, then we compute the probability of a given failure to occur within a time interval upon the occurrence of a particular pattern of preceding failures. Due to the nature of the failure data, in which the failure types must be handled as categorical variables, we used the logistic regression method to tackle our research problem — especially its variant multinomial logistic regression. Our approach was able to predict OS failures with good to high accuracy (81% to 95%). The resulting regression models proved robust enough to deal with different prediction time intervals with no degrading effect on their accuracy.
Palavras-chave:
statistical association, failure patterns, prediction
Referências
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C.A.R. Dos Santos R. Matias and K. S. Trivedi "An Empirical Exploratory Analysis of Failure Sequences in a Commodity Operating System" Proc. of the Brazilian Symposium on Computing Systems Engineering 2019.
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A. Chou J. Yang B. Chelf S. Hallem and D. Engler "An empirical study of operating systems errors" Proc. of the ACM Symp. on Operating Systems Principles pp. 73-88 2001.
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A. Ganapathi V. Ganapathi and D. Patterson "Windows XP kernel crash analysis" Proc. of the Conference on Large Installation System Administration pp. 149-159 2006.
K. Goseva-Popstojanova and K. Trivedi "Failure Correlation in Software Reliability Models" IEEE Trans. On Reliability vol. 49 pp. 37-48 March 2000.
A. Nikora and M. Lyu "Software Reliability Measurement Experience" in Handbook of Software Reliability Engineering McGraw-Hill 1996.
Y. Liang Y. Zhang A. Sivasubramaniam M. Jette and R. Sahoo "BlueGene/L Failure Analysis and Prediction Models" Proc. International Conference on Dependable Systems and Networks pp. 425-434 2006.
A. Fronza G. Sillitti M. Succi and J. Vlasenko Terho "Failure Prediction Based on Log Files Using Random Indexing and Support Vector Machines" J. Systems and Software vol. 86 no. 1 pp. 2-11 January 2013.
C. Jee and T. Macaulay Top software failures in recent history.
R. Charette The Biggest IT Failures of 2018.
M. Sullivan and R. Chillarege "Software defects and their impact on system availability - a study of field failures in operating systems" Proc. of the Int'l Symp. on Fault-Tolerant Computing pp. 2-9 1991.
Z. Li L. Tan X. Wang S. Lu Y. Zhou and C. Zhai "Have things changed now? An empirical study of bug characteristics in modern open source software" Proc. of the Workshop on Architectural and System Support for Improving Sw. Dependability pp. 25-33 2006.
C.A.R. Dos and R. Matias "Failure Patterns in Operating Systems: An Exploratory and Observational Study" Elsevier Journal of Systems and Software vol. 137 pp. 512-530 March 2018.
C.A.R. Dos Santos R. Matias and K. S. Trivedi "An Empirical Exploratory Analysis of Failure Sequences in a Commodity Operating System" Proc. of the Brazilian Symposium on Computing Systems Engineering 2019.
N. Altman and M. Krzywinski "Points of significance: association correlation and causation" Nature Methods vol. 12 pp. 899-900 September 2015.
A. Avižicnis J.-C. Laprie B. Randell and C. Landwehr "Basic Concepts and Taxonomy of Dependable and Secure Computing" IEEE Trans. on Dependable and Secure Comp. vol. 1 pp. 11-33 October 2004.
R. Lai Huawei reveals HarmonyOS its alternative to Android.
M. M. Swift B. N. Bershad and H. M. Levy "Improving the reliability of commodity operating systems" Proc. of the ACM Symposium on Operating Systems Principles pp. 207-222 2003.
A. Chou J. Yang B. Chelf S. Hallem and D. Engler "An empirical study of operating systems errors" Proc. of the ACM Symp. on Operating Systems Principles pp. 73-88 2001.
A. Ganapathi and D. Patterson "Crash data collection: a Windows case study" Proc. of the Int'l Conference on Dependable Systems and Networks pp. 280-285 2005.
R. Matias G. Oliveira and L. Araujo "Operating system reliability from the quality of experience viewpoint: an exploratory study" Proc. of the ACM Symp. on Applied Comp. pp. 1644-1649 2013.
C.A.R. Dos Santos M. Antunes R. Matias L. Assunção and V. Maciel "Reliability Assessment of Commercial Off-the-Shelf Operating System Software: An Empirical Study" Proc. of the Brazilian Symp. on Computing Systems Engineering 2018.
C. Bird V.P. Ranganath T. Zimmermann N. Nagappan and A. Zeller "Extrinsic Influence Factors in Software Reliability: A Study of 200000 Windows Machines" Proc. 36th International Conference on Software Engineering pp. 205-214 2014.
"Microsoft Security Essentials" Microsoft [online] Available: https://www.microsoft.com/en-us/download/details.aspx?id=5201.
M. Golemati A. Katifori E. Giannopoulou I. Daradimos and C. Vassilakis "Evaluating the significance of the Windows Explorer visualization in personal information management browsing tasks" Proc. of Int'l Conf. on Information Visualization pp. 93-100 2007.
"Windows Error Reporting" Microsoft [online] Available: http://msdn.microsoft.com/en-us/library/bb513613(v=vs.85).aspx.
"Windows Installer" Microsoft [online] Available: http://msn.microsot.com/n-us/library/cc185688%28VS.85%29.aspx.
"Desktop Operating System Market Share" NetMarketShare 2020 [online] Available: https://netmarketshare.com/operating-system-market-share.aspx?id=platformsDesktopVersions.
"Reliability analysis component" Microsoft [online] Available: http://technet.microsoft.com/en-us/library/cc774636(v=ws.10).aspx.
"Win_32 ReliabilityRecord class" Microsoft [online] Available: https://msdn.microsoft.com/en-us/library/windows/desktop/ee706630%28v=vs.85%29.aspx?f=255&MSPPError=-2147217396.
B. Desharnais F. Camirand-Lemyre P. Mireault and C. Skinner "Determination of confidence intervals in non-normal data: application of the bootstrap to cocaine concentration in femoral blood" J. of analytical toxicology vol. 39 pp. 113-117 March 2015.
D. Hosmer S. Lemeshow and R. Sturdivant Applied Logistic Regression John Wiley & Sons 2013.
H-J Andreß K. Golsch and A. Schmidt Applied Panel Data Analysis for Economic and Social Surveys Springer 2013.
K. Pituch and J. Stevens Applied Multivariate Statistics for the Social Sciences: Analyses with SAS and SPSS Routledge 2015.
D. McFadden "Conditional logit analysis of qualitative choice behavior" Frontiers in Econometrics pp. 105-142 1974.
A. Ganapathi V. Ganapathi and D. Patterson "Windows XP kernel crash analysis" Proc. of the Conference on Large Installation System Administration pp. 149-159 2006.
K. Goseva-Popstojanova and K. Trivedi "Failure Correlation in Software Reliability Models" IEEE Trans. On Reliability vol. 49 pp. 37-48 March 2000.
A. Nikora and M. Lyu "Software Reliability Measurement Experience" in Handbook of Software Reliability Engineering McGraw-Hill 1996.
Y. Liang Y. Zhang A. Sivasubramaniam M. Jette and R. Sahoo "BlueGene/L Failure Analysis and Prediction Models" Proc. International Conference on Dependable Systems and Networks pp. 425-434 2006.
A. Fronza G. Sillitti M. Succi and J. Vlasenko Terho "Failure Prediction Based on Log Files Using Random Indexing and Support Vector Machines" J. Systems and Software vol. 86 no. 1 pp. 2-11 January 2013.
Publicado
23/11/2020
Como Citar
DOS SANTOS, Caio; MATIAS, Rivalino; TRIVEDI, Kishor.
A Statistical Approach to Predict Operating System Failures Based on Multiple Failures Association. In: SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SISTEMAS COMPUTACIONAIS (SBESC), 10. , 2020, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 206-213.
ISSN 2237-5430.
