摘要
随着软件系统规模的不断扩大和复杂程度的日益加大,从20世纪60年代末期开始,出现了以大量软件项目进度延期、预算超支和质量缺陷为典型特征的软件危机。在对软件项目进行估算时,通常情况下能得到相关软件组织或软件产品的某些历史数据,充分利用这些历史数据对预测与估算软件项目是很有帮助的。稳健回归分析(RRA),就是这样一种相当常用与有效的数据驱动方法。在比较、回顾一些稳健回归分析研究成果的基础上,重点解决了软件成本估算数据用传统回归分析存在的问题,并有效地解决了由于异常数据存在而产生的掩蔽效应。同时尝试提出在软件成本数据估算中运用稳健回归方法进行系统而全面的仿真实验分析,发现该方法能有效地解决异常数据的掩蔽效应,得到比较满意的结果。
Along with the unceasing expansion and the complex degree daily enlarging of the software system scale, it appears the typical software crisis such as the massive software project progress extension, the budget overspending and the quality flaw from the 20th century 60＇s last stages. The correlated software organization or the software product certain historical data can obtain carry on the estimation of the software project in the usual situation, and it is helpful to take advantage of these data to forecast the future software projects. The robust regression analysis （RRA） is such one kind quite commonly used and the effective data actuation method. Based on some retrospective studies of RRA, focuses on some problems of the software cost estimation data with ordinary methods and tries to propose the RRA methods to analysis of the software development cost estimation problem of masking effects when the outliers exist. The results are found that this masking effects by outliers and obtained better results. data and effectively solutes to the method could solve effectively the masking effects by outliers and obtained better results.
出处
《科学技术与工程》
2008年第17期4864-4868,共5页
Science Technology and Engineering
关键词
软件成本估计
稳健估计
回归分析
异常数据检测
M估计量
software cost estimation robust estimate regression analysis outlier examination M-estimator
