Journal of Software:2015.26(4):886-903

(浙江理工大学 信息学院, 浙江 杭州 310018;浙江理工大学 理学院, 浙江 杭州 310018)
Improving Software Reliability Based on Online Fault Localization and Self-Adaption
YANG Xiao-Yan,ZHOU Yuan,DING Zuo-Hua
(School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China;School of Science, Zhejiang Sci-Tech University, Hangzhou 310018, China)
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Received:August 12, 2014    Revised:October 14, 2014
> 中文摘要: 可靠性是衡量软件质量的一个重要指标.在线预测和提高软件可靠性是一个重要的研究课题.目前大多数在线预测和提高软件可靠性的方法具有如下弱点:不能预测软件不同时段的可靠性,且不能定位导致可靠性下降的组件.针对服务组合软件系统,提出在线提高可靠性的方法.通过观测端口失效数据,预测在线系统在不同时段的可靠性.当预测到的可靠性低于预期时,则采用改进的基于频谱的错误定位方法,定位出导致问题的故障组件,再通过添加新组件或替换故障组件的方法对软件系统重新配置,从而在线自动提高软件系统可靠性.使用在线商店的事例来说明方法的有效性.
Abstract:Reliability is an important index to measure the quality of software. Online predicting and improving software reliability are an important research topic. Most existing methods have the following weakness: They can neither predict software reliability on different time intervals nor locate the faulty components that cause the declining of the reliability. This paper proposes a new method to online improve reliability for service composition. The method uses the monitored failure data at ports to predict the reliabilities of service composition on different time intervals. If the predicted reliability is lower than the expected value, it then locates the faulty component that causes the declining of the reliability by using an improved spectrum-fault-localization method. The system is automatically reconfigured by adding a new component or replacing the faulty component to improve the system reliability. An online shop example is used to demonstrate the effectiveness of the proposed method.
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基金项目:国家自然科学基金(61210004, 61170015) 国家自然科学基金(61210004, 61170015)
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YANG Xiao-Yan,ZHOU Yuan,DING Zuo-Hua.Improving Software Reliability Based on Online Fault Localization and Self-Adaption.Journal of Software,2015,26(4):886-903