Evaluation of project quality: a DEA-Based approach

Authors:
Shen Zhang;Yongji Wang;Jie Tong;Jinhui Zhou;Li Ruan
Affiliations:
Laboratory for Internet Software Technologies, Institute of Software, The Chinese Academy of Sciences, Beijing, China;Laboratory for Internet Software Technologies, Institute of Software, The Chinese Academy of Sciences, Beijing, China;Laboratory for Internet Software Technologies, Institute of Software, The Chinese Academy of Sciences, Beijing, China;Laboratory for Internet Software Technologies, Institute of Software, The Chinese Academy of Sciences, Beijing, China;Laboratory for Internet Software Technologies, Institute of Software, The Chinese Academy of Sciences, Beijing, China
Venue:
SPW/ProSim'06 Proceedings of the 2006 international conference on Software Process Simulation and Modeling
Year:
2006

Citing 4
Cited 2

Identifying High Performance ERP Projects

IEEE Transactions on Software Engineering
Some Misconceptions About Lines of Code

METRICS '97 Proceedings of the 4th International Symposium on Software Metrics
Module Size Distribution and Defect Density

ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Open Source Software Development: A Case Study of FreeBSD

METRICS '04 Proceedings of the Software Metrics, 10th International Symposium

Capability assessment of individual software development processes using software repositories and DEA

ICSP'08 Proceedings of the Software process, 2008 international conference on Making globally distributed software development a success story
Creating Process-Agents incrementally by mining process asset library

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

The evaluation of project quality exhibits multivariable, VRS (variable return to scale) and decision maker's preference properties. In this paper, we present a Data Envelopment Analysis (DEA) based evaluation approach. The DEA VRS model, which handles multivariable and VRSeffectively, is used to measure project quality. And the DEA cone ratio model, which utilizes Analytical Hierarchy Process (AHP) to constrain quality metrics with respect to decision maker's preference, is also adopted to analyze the return to scaleof the projects. A case study, which assesses 10 projects from ITECHS and 20 “Top active” projects on sourceforge.net with the novel method, is demonstrated. The results indicate that our approach is effective for quality evaluation and can get accurate estimates of future possible improvements.