A Covariate Software Reliability Model and Optimal Test Activity Allocation
A Covariate Software Reliability Model and Optimal Test Activity Allocation
复制标题
协变量软件可靠性模型和最优测试活动分配
DOI：
10.1016/j.jss.2020.110643
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
and Fiondella, L.
中科院分区：
文献类型：
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作者：
Nagaraju, V.;Jayasinghe, C.;and Fiondella, L.
传统的软件可靠性增长模型，使定量评估的软件测试过程中的故障检测的测试时间或努力。然而，这些模型中的大多数并不确定具体的测试活动的基础故障发现，因此只能提供有限的指导如何逐步分配的努力。虽然有一些新的研究集中在协变量软件可靠性增长模型，他们仅限于模型的开发，应用和评估。基于离散考克斯比例风险模型，提出了一种包含协变量的非齐次泊松过程软件可靠性增长模型。应用一种高效稳定的期望条件最大化算法辨识模型参数。一个最优的测试活动分配问题，制定最大限度地发现故障。所提出的方法是通过数值例子说明从文献中的数据集。
Traditional software reliability growth models enable quantitative assessment of the software testing process by characterizing fault detection in terms of testing time or effort. However, the majority of these models do not identify specific testing activities underlying fault discovery and thus can only provide limited guidance on how to incrementally allocate effort. Although there are several novel studies focused on covariate software reliability growth models, they are limited to model development, application, and assessment. This paper presents a non-homogeneous Poisson process software reliability growth model incorporating covariates based on the discrete Cox proportional hazards model. An efficient and stable expectation conditional maximization algorithm is applied to identify the model parameters. An optimal test activity allocation problem is formulated to maximize fault discovery. The proposed method is illustrated through numerical examples on a data set from the literature.