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

Hiroyuki Okamura () and Tadashi Dohi ()
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Hiroyuki Okamura: Graduate School of Engineering, Hiroshima University
Tadashi Dohi: Graduate School of Engineering, Hiroshima University

A chapter in Stochastic Reliability and Maintenance Modeling, 2013, pp 285-313 from Springer

Abstract: 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.

Keywords: Failure Time Distribution; Software Reliability Models (SRMs); Nonhomogeneous Poisson Process (NHPPs); NHPP Model; Mean Value Function (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-1-4471-4971-2_13

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DOI: 10.1007/978-1-4471-4971-2_13

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