Software reliability growth models with normal failure time distributions
Software reliability growth models with normal failure time distributions
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DOI：
10.1016/j.ress.2012.02.002
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发表时间：
2013-08
期刊：
影响因子：
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通讯作者：
H. Okamura;T. Dohi;S. Osaki
中科院分区：
文献类型：
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作者：
H. Okamura;T. Dohi;S. Osaki
提出了软件失效时间服从正态分布的软件可靠性增长模型。所提出的模型在数学上易于处理，并且具有足够的拟合软件故障数据的能力。特别地，我们考虑了正态分布的SRGM的参数估计算法。所开发的算法是基于EM（期望最大化）算法，是相当简单的软件应用程序的实施。通过对真实的软件项目中收集的16种失效时间数据进行数值实验，考察了正态分布的SRGMs的拟合能力。
This paper proposes software reliability growth models (SRGM) where the software failure time follows a normal distribution. The proposed model is mathematically tractable and has sufficient ability of fitting to the software failure data. In particular, we consider the parameter estimation algorithm for the SRGM with normal distribution. The developed algorithm is based on an EM (expectation-maximization) algorithm and is quite simple for implementation as software application. Numerical experiment is devoted to investigating the fitting ability of the SRGMs with normal distribution through 16 types of failure time data collected in real software projects.