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Application of EM Algorithm to NHPP-Based Software Reliability Assessment with Ungrouped Failure Time Data

In: Stochastic Reliability and Maintenance Modeling

Author

Listed:
  • Hiroyuki Okamura

    (Graduate School of Engineering, Hiroshima University)

  • Tadashi Dohi

    (Graduate School of Engineering, Hiroshima University)

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.

Suggested Citation

  • Hiroyuki Okamura & Tadashi Dohi, 2013. "Application of EM Algorithm to NHPP-Based Software Reliability Assessment with Ungrouped Failure Time Data," Springer Series in Reliability Engineering, in: Tadashi Dohi & Toshio Nakagawa (ed.), Stochastic Reliability and Maintenance Modeling, edition 127, pages 285-313, Springer.
    • Handle: RePEc:spr:ssrchp:978-1-4471-4971-2_13
    DOI: 10.1007/978-1-4471-4971-2_13
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    Cited by:

    1. Hiroyuki Okamura & Tadashi Dohi, 2021. "Application of EM Algorithm to NHPP-Based Software Reliability Assessment with Generalized Failure Count Data," Mathematics, MDPI, vol. 9(9), pages 1-18, April.

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