A Novel Approach to Quantifying the Influence of Software Process on Project Performance

摘要：

Determining the appropriate process to be used is a key ingredient of project management. To this end, understanding the influence of activities on the project performance can facilitate the project management. However, quantifying such a relationship via traditional Multiple Linear Regression method tends to be challenging, for the amount of independent variables (activities in software process) is usually larger than the size of dataset. Aiming at such a problem, in this paper we propose a novel approach. By combing the Dantzig selector and Ordinary Least Squares (OLS) regression method, our approach can derive the regression model in such challenging situations, which further set the theoretical stage for studying the quantitive influences of software process on project performance.

作者: Jia-kuan Ma Xiao-fan Tong Ya-sha Wang Gang Li

作者单位: Key Laboratory of High Confidence Software Technologies, Ministry of Education Beijing, China;Softwa Shandong Computer Science Center, Jinan, China ;Shandong Provincial Key Laboratory of Computer Netwo

会议类型: 国际会议

会议名称: 13th International Conference on Enterprise Information System(第13届企业信息系统国际会议 ICEIS 2011)

会议地点: 北京

会议语种:英文

页码: 1616-1622

在线出版日期: 2011-06-08（万方平台首次上网日期，不代表论文的发表时间）