An estimation of software reliability models based on EM algorithm

Author(s):  
Hiroyuki Okamura ◽  
Yasuhiro Watanabe ◽  
Tadashi Dohi ◽  
Shunji Osaki
Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 985
Author(s):  
Hiroyuki Okamura ◽  
Tadashi Dohi

Software reliability models (SRMs) are widely used for quantitative evaluation of software reliability by estimating model parameters from failure data observed in the testing phase. In particular, non-homogeneous Poisson process (NHPP)-based SRMs are the most popular because of their mathematical tractability. In this paper, we focus on the parameter estimation algorithm for NHPP-based SRMs and discuss the EM algorithm for generalized fault count data. The presented algorithm can be applied for failure time data, failure count data, and their mixture. The paper derives the EM-step formulas for basic 12 NHPP-based SRMs and demonstrate a numerical experiment to present the convergence property of our algorithms. The developed algorithms are suitable for an automatic tool for software reliability evaluation.


Author(s):  
Milos Milovancevic ◽  
Aleksandar Dimov ◽  
Kamen Boyanov Spasov ◽  
Ljubomir Vračar ◽  
Miroslav Planić

1997 ◽  
Vol 29 (2) ◽  
pp. 337-352 ◽  
Author(s):  
Yiping Chen ◽  
Nozer D. Singpurwalla

Assessing the reliability of computer software has been an active area of research in computer science for the past twenty years. To date, well over a hundred probability models for software reliability have been proposed. These models have been motivated by seemingly unrelated arguments and have been the subject of active debate and discussion. In the meantime, the search for an ideal model continues to be pursued. The purpose of this paper is to point out that practically all the proposed models for software reliability are special cases of self-exciting point processes. This perspective unifies the very diverse approaches to modeling reliability growth and provides a common structure under which problems of software reliability can be discussed.


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