Analysis of Failure Count Data Based on NHPP Models 


Vol. 4,  No. 2, pp. 395-400, Feb.  1997
10.3745/KIPSTE.1997.4.2.395


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  Abstract

An important quality characteristic of a software is the software reliability. Software reliability growth models provide the tools to evaluate and monitor the reliability growth behavior of the software during the testing phase. Therefore failure data collected during the testing phase should be continuously analyzed on the basis of some selected software reliability growth models. For the cases where nonhomogeneous Poisson process models are the candidate models, we suggest Poisson regression model, which expresses the relationship between the expected and actual failures counts in disjoint time intervals, for analyzing the failure count data. The weighted least squares method is then used to estimate the parameters in the model. The resulting estimators are equivalent to the maximum likelihood estimators. The method is illustrated by analyzing the failure count data gathered from a large-scale switching system.

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[IEEE Style]

K. S. Hee, J. H. Sook, K. Y. Soon, P. J. Yang, "Analysis of Failure Count Data Based on NHPP Models," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 4, no. 2, pp. 395-400, 1997. DOI: 10.3745/KIPSTE.1997.4.2.395.

[ACM Style]

Kim Seong Hee, Jeong Hyang Sook, Kim Young Soon, and Park Joong Yang. 1997. Analysis of Failure Count Data Based on NHPP Models. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 4, 2, (1997), 395-400. DOI: 10.3745/KIPSTE.1997.4.2.395.

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