Confidence interval estimation of NHPP-based software reliability models
Confidence interval estimation of NHPP-based software reliability models
复制标题
基于NHPP的软件可靠性模型的置信区间估计
DOI：
10.1109/issre.1999.809305
复制
发表时间：
1999
期刊：
影响因子：
--
通讯作者：
Kishor S. Trivedi
中科院分区：
文献类型：
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作者：
Liang Yin;Kishor S. Trivedi
软件可靠性增长模型，如非齐次泊松过程（NHPP）模型，是软件可靠性预测中常用的模型。在这些模型中，参数的估计通常是通过点估计来完成的。然而，这种方法会产生一些数值问题，并使实际计算困难，特别是对于自动可靠性预测工具。本文研究了Goel-Okumoto（1979）模型和S形模型（S. Yamada等人，1983年）。可以得到参数的上界和下界。对于可靠性预测，我们实现了一个简化的贝叶斯方法，它提供了改进的结果。还计算了预测可靠性的界限。此外，在早期的点估计方法中遇到的数值问题，通过这种方法被删除。因此，我们的研究结果可以作为软件质量评估的一个重要组成部分。
Software reliability growth models, such as the non-homogeneous Poisson process (NHPP) models, are frequently used in software reliability prediction. The estimation of parameters in these models is often done by point estimation. However, some numerical problems arise with this approach, and make the actual computation hard, especially for automated reliability prediction tools. In this paper, confidence interval computation is studied in the Goel-Okumoto (1979) model and the S-shaped model (S. Yamada et al., 1983). The upper and the lower bounds of the parameters can be obtained. For reliability prediction, we implement a simplified Bayesian approach, which delivers improved results. The bounds on the predicted reliability are also computed. Furthermore, the numerical problems encountered in earlier point estimation methods are removed by this approach. Our results can thus be used as an important part of the assessment of software quality.