基于重大偏差标准的软件项目工作量管理方法研究

中国管理科学 ›› 2013, Vol. ›› Issue (2): 161-167.

基于重大偏差标准的软件项目工作量管理方法研究

张俊光, 杨芳芳, 杨双

北京科技大学东凌经济管理学院, 北京 100083

收稿日期:2011-06-11 修回日期:2012-10-17 出版日期:2013-04-30 发布日期:2013-04-25
基金资助:
教育部人文社科基金(10YJC630384);中央高校基本科研业务费项目(FRF-BR-12-020,FRF-BR-12-007)

Study of Software Project Effort Estimating and Monitoring Based on Significant Deviation Standard

ZHANG Jun-guang, YANG Fang-fang, YANG Shuang

Dongling School of Economics and Management, University of Science and Technology, Beijing 100083, China

Received:2011-06-11 Revised:2012-10-17 Online:2013-04-30 Published:2013-04-25

摘要/Abstract

摘要： 为有效管理软件项目工作量,本文研究了一个基于重大偏差标准的软件项目工作量管理模型。该模型利用过程控制的原理和数理统计的方法,提出依据重大偏差标准和风险储备时间对软件项目进行动态控制,并介绍了风险储备时间与重大偏差标准的定量设置方法。该模型涵盖了从风险储备时间的确定,到重大偏差标准的提出,再根据风险储备时间和重大偏差标准进行监控的整个过程。为提高软件项目管理精度,保证项目在可接受的偏差范围内顺利完成打下坚实的基础。

关键词: 项目管理, 估计, 重大偏差标准, 风险储备时间, 监控

Abstract: For the effective management of software project effort, a management model of software project effort is studied based on significant deviation standard. According to the principle of process control and statistical methods, dynamic controlling of software project based on significant deviation standard and risk reserve time is put forward, and quantitative methods on how to define risk reserve time and significant deviation standard are introduced. The model covers the whole process of defining risk reserve time, determining a significant standard deviation, and monitoring and controlling according to the risk reserve time and the significant deviation standard. It lays the foundation to improve the accuracy of software project management and to ensure the successful completion of the project within the acceptable deviation.

Key words: project management, estimation, significant deviation standard, risk reserve time, monitoring and controlling

中图分类号:

TP311.5

张俊光, 杨芳芳, 杨双. 基于重大偏差标准的软件项目工作量管理方法研究[J]. 中国管理科学, 2013, (2): 161-167.

ZHANG Jun-guang, YANG Fang-fang, YANG Shuang. Study of Software Project Effort Estimating and Monitoring Based on Significant Deviation Standard[J]. Chinese Journal of Management Science, 2013, (2): 161-167.

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