Title :
Towards Adaptive Project Tracking using Individual Productivity Metrics
Author_Institution :
Zhejiang Gongshang Univ., Hangzhou
Abstract :
Quality and productivity are two of the most important factors in software development. Quality based software productivity improvement is essential for the software process improvement. In this paper, quality recognition mechanism and individual productivity metrics are suggested to avoid the large effort in typical measurement of productivity and quality in daily project. A framework using individual productivity metrics is designed to achieve adaptive software project tracking in legacy system reengineering projects.
Keywords :
software development management; software metrics; software process improvement; software quality; individual software productivity metrics; project tracking; quality recognition mechanism; software development; software process improvement; Cybernetics; Feedback; ISO standards; Job shop scheduling; Machine learning; Productivity; Programming; Software quality; Software testing; System testing; Adaptive software project tracking; Extreme programming; Individual software productivity metrics; Software productivity; Software quality;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370590
