软件可靠性预测的核函数方法  

Kernel Methods of Software Reliability Prediction

作　　者：楼俊钢[1] 申情[1] 沈张果[1] 

机构地区：[1]湖州师范学院信息与工程学院,湖州313000

出　　处：《计算机科学》2012年第4期145-148,共4页Computer Science

基　　金：国家自然科学基金(61103051);浙江省自然科学基金(Y1101237)资助

摘　　要：通过合理的假设和抽象,把软件可靠性预测问题转化成从高维空间向低维空间的非线性映射,采用核函数回归估计理论对软件失效时间数据之间的对应关系进行建模,在新建立的模型中,随着软件失效不断发生,模型参数将不断自动调整以适应失效过程的动态变化,从而实现软件可靠性的自适应预测,并对模型中核函数以及回归估计算法的选择进行了研究。最后,对14个软件失效数据集进行了实验分析,并对新建模型与部分其它模型的预测能力和适用能力进行了比较。The pridiction of future failure data from observed data sets can been transformed into a problem of nolinear regression,and the kernel functions method is very efficient for solving nolinear regression problems.A kernel functions-based generic model adaptive to the characteristic of the given data sets is used for software failure time prediction,and it is applied to learn and recognize the inherent internal temporal property of software failure sequence in order to capture the most current feature hidden inside the software failure behavior.The experimental results based on fourteen real data sets show that the proposed model has better prediction and applicability than that of some other conditional software reliability prediction models.

关 键 词：核函数 核函数回归算法 软件可靠性模型 非齐次泊松过程模型 

分 类 号：TP302.7[自动化与计算机技术—计算机系统结构]