S-shaped software reliability growth models with four types of software error data
S-shaped software reliability growth models with four types of software error data
复制标题
具有四种软件错误数据的S形软件可靠性增长模型
DOI：
10.1080/00207728308926488
复制
发表时间：
1983
影响因子：
4.3
通讯作者：
S. Osaki
中科院分区：
文献类型：
--
作者：
S. Yamada;S. Osaki
一般来说，我们应该对观察到的数据应用最合适的统计推断。在本文中，我们的兴趣是对软件可靠性增长模型的观测数据进行统计推断，该模型由具有S形均值函数的非齐次泊松过程描述。我们应该从审查和删除的角度来考虑这些观察到的数据。当测试在检测到指定数量的错误或指定时间时停止时，就会进行审查。删除指定数量的检测到的错误或在指定时间之前删除检测到的错误总数时，将发生删除。通过删减和剔除对软件错误数据类型进行分类，我们可以考虑四种类型的观测数据。对于四类观测数据，我们给出了模型中参数的极大似然估计。并讨论了参数的渐近分布。
In general, we should apply the most suitably statistical inferences to observed data. In this paper, our interests are statistical inferences on the observed data of software reliability growth models described by a non-homogeneous Poisson process having an S-shaped mean value function. We should consider such observed data in terms of censoring and removing. Censoring occurs when the test is stopped at detection of a specified number of errors or a specified time. Removing occurs when a specified number of detected errors or a total number of detected errors up to a specified time are removed. Classifying the types of software error data by censoring and removing, we can consider four types of the observed data. We give the maximum likelihood estimates of parameters in the models for four types of the observed data. The asymptotic distributions of the parameters are also discussed.