BP人工神经网络在bug分析中的应用  

Application of back propagation artificial neural networks in bug analysis

作　　者：王雷[1] 杨小虎[1] 

机构地区：[1]浙江大学计算机科学与技术学院,杭州310015

出　　处：《计算机应用》2010年第1期153-155,共3页journal of Computer Applications

摘　　要：应用于金融领域的软件系统,由于其包含复杂的商业逻辑导致此类系统不但庞大而且逻辑复杂。在此类系统的开发和升级过程中,系统缺陷及错误的寻找、分析常常非常困难且费时,在通常情况下,它往往成为整个项目中后期的瓶颈。运用BP人工神经网络的算法,设计并实现了针对某银行网上交易系统的缺陷及错误分析系统,并且通过实验证实该系统能帮助开发人员提高寻找、分析系统缺陷及错误的效率,进而加快整个项目的进度。Due to the complex business requirements, financial software system could be giant in scope and complex in system logic. During the development and maintenance of such software system, the detection and analysis of the system defects and errors are difficult and time-consuming in most of the circumstances, which usually is deemed as the bottleneck of the whole project after the mid-stage. In this paper, by implementing the Back Propagation （BP） algorithm, a defect analysis system was designed for the enhancement project of an Internet-based transaction trading system. The experimental results show that it does improve the developers＇ efficiency and productivity in defect detecting and fixing, which consequentially accelerates the project progress.

关 键 词：BP人工神经网络 系统升级 bug分析 金融软件系统 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]