The Bayesian Analysis for Software Reliability Models Based on NHPP


The KIPS Transactions:PartD, Vol. 10, No. 5, pp. 805-812, Aug. 2003
10.3745/KIPSTD.2003.10.5.805,   PDF Download:

Abstract

This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP) and performs Bayesian inference using prior imformation. The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. The parametric inferences of the model using Logarithmic Poisson model, Crow model and Rayleigh model is discussed. Bayesian computation and model selection using the sum of squared errors. The numerical results of this models are applied to real software failure data. Tools of parameter inference was used method of Gibbs sampling and Metropolis algorithm. The numerical example by T1 data (Musa) was illustrated.


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Cite this article
[IEEE Style]
L. S. Sig, K. H. Cheol, S. Y. Jae, "The Bayesian Analysis for Software Reliability Models Based on NHPP," The KIPS Transactions:PartD, vol. 10, no. 5, pp. 805-812, 2003. DOI: 10.3745/KIPSTD.2003.10.5.805.

[ACM Style]
Lee Sang Sig, Kim Hui Cheol, and Song Yeong Jae. 2003. The Bayesian Analysis for Software Reliability Models Based on NHPP. The KIPS Transactions:PartD, 10, 5, (2003), 805-812. DOI: 10.3745/KIPSTD.2003.10.5.805.