Abstract
This chapter presents computation procedures for maximum likelihood estimates (MLEs) of software reliability models (SRMs) based on nonhomogeneous Poisson processes (NHPPs). The idea behind our methods is to regard usual failure time data as incomplete data. This leads to quite simple computation procedures for NHPP-based SRMs based on the EM (expectation–maximization) algorithm, and these algorithms overcome a problem arising in practical use of SRMs. In this chapter, we discuss the algorithms for 10 types of NHPP-based SRMs. Numerical examples show that the proposed EM algorithms help us to reduce computational efforts in the parameter estimation of NHPP-based SRMs.
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Acknowledgments
This research was supported by the Ministry of Education, Science, Sports and Culture, Grant-in-Aid for Scientific Research (C), Grant No. 23500047 (2011–2013) and Grant No. 23510171 (2011–2013). The authors are grateful to Prof. Shunji Osaki and his teaching. Everything he teaches was valuable for our lives as well as research activities.
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Appendix
Appendix
1.1 Derivation of Eq. (40)
For notational simplification, \(\mathrm{{E}}[\cdot | D_T; \omega , \varvec{\lambda }]\) is written by \(\mathrm{{E}}[\cdot |D_T]\). From the left-hand side of Eq. (40), we have
Since \(T_1, \ldots , T_N\) are IID samples, the first term of right-hand side of the above equation can be easily obtained. Then we focus on the derivation of the second term of right-hand side of Eq. (40). From the posterior distribution of \(N\), we obtain
where \(r\) corresponds to the number of failures experienced after time \(T\). The integrals in Eq. (133) can be changed to
and
By canceling the constants of numerator and denominator, Eq. (133) is reduced to
1.2 Derivation of Eq. (56)
From the left-hand side of Eq. (56), we have
Similar to the previous section, we consider the second and third terms of right-hand side of Eq. (137). Then we have
and
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Okamura, H., Dohi, T. (2013). Application of EM Algorithm to NHPP-Based Software Reliability Assessment with Ungrouped Failure Time Data. In: Dohi, T., Nakagawa, T. (eds) Stochastic Reliability and Maintenance Modeling. Springer Series in Reliability Engineering, vol 9. Springer, London. https://doi.org/10.1007/978-1-4471-4971-2_13
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