The Implementation of Artificial Neural Networks Applying to Software Reliability Modeling
会议名称：《2009中国控制与决策会议》
会议日期：2009年
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 081202[工学-计算机软件与理论]
基 金：the National ScienceCouncil Taiwan R.O.C. under NSC 97-2221-E-431-002
关 键 词：Artificial Neural Network Non-Homogeneous Poisson Process(NHPP) Software Reliability Growth Models(SRGMs) Software Testing
摘 要：In current software reliability modeling research,the main concern is how to develop general prediction *** this paper,we propose several improvements on the conventional software reliability growth models (SRGMs) to describe actual software development process by eliminating some unrealistic *** of these models have focused on the failure detection process and not given equal priority to modeling the fault correction ***,most latent software errors may remain uncorrected for a long time even after they are detected,which increases their *** remaining software faults are often one of the most unreliable reasons for software quality. Therefore,we develop a general framework of the modeling of the failure detection and fault correction processes. Furthermore,we apply neural network with back-propagation to match the histories of software failure *** will also illustrate how to construct the neural networks from the mathematical viewpoints of software reliability modeling in ***,numerical examples are shown to illustrate the results of the integration of the detection and correction process in terms of predictive ability and some other standard criteria.