Robustness of Non-homogeneous Gamma Process-based Software Reliability Models

被引:5
|
作者
Saito, Yasuhiro [1 ]
Dohi, Tadashi [1 ]
机构
[1] Hiroshima Univ, Dept Informat Engn, Higashihiroshima, Japan
来源
2015 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE SECURITY AND RELIABILITY (QRS 2015) | 2015年
关键词
Non-homogeneous gamma process; Software reliability; Non-parametric maximum likelihood estimation; Non-homogeneous Poisson process; Goodness-of-fit performance; POISSON; TREND;
D O I
10.1109/QRS.2015.21
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In this paper we extend non-homogeneous gamma process (NHGP)-based software reliability models (SRMs) by Ishii and Dohi (2008) from both view points of modeling and parameter estimation. In modeling, we generalize the underlying NHGP-based SRMs to those for eleven kinds of trend function, which can characterize a variety of software fault-detection patterns. In parameter estimation, we develop a non-parametric maximum likelihood estimation method without the complete knowledge on trend functions, and compare it with the parametric maximum likelihood estimation method. Since an NHGP involves a non-homogeneous Poisson processes (NHPPs) as the simplest case, it is shown that NHGP-based SRMs are much more robust than the common NHPP-based SRMs and that our non-parametric method can improve the goodness-of-fit performance of the conventional parametric one.
引用
收藏
页码:75 / 84
页数:10
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