A common problem in software fault prediction is presence of the noise in the data.
软件失效预测中的一个普遍问题是数据中噪声的存在。
Based on JM model, we propose a software reliability prediction model involving fault-remove time which followed exponential distribution.
因此在JM模型的基础上，提出了排错时间为负指数分布的软件可靠性模型及本模型的极大似然参数估计方法。
With software fault severity considered, a software fault-proneness prediction model is proposed in this paper by Support Vector Machine and the Chidamber-Kemerer(C&K)object-oriented metrics.
本文考虑软件故障严重程度，并采用C&K面向对象度量集，以支持向量机分析方法为数学工具，建立一种基于面向对象软件易发性故障预测模型。
应用推荐