Statistical Analysis Based on Software Process Data and Quantitative Project Evaluation  
Author Shigeru Yamada


Co-Author(s) Makoto Shiomi


Abstract Many risks due to human factors are latent in a software development project. If suitable management can be performed to these risks and a software development process can be improved continuously, we will lead the project to improve in the productivity and quality of software product. In this paper, we analyze the process data collected from an actual software development project, and clarify the process factors which affect the quality of software product, based on multivariate analysis. Further, we also discuss a method of quantitative project evaluation, which helps us to give useful quantitative measures for determining project completion.


Keywords Principal Component Analysis, Multiple Regression Analysis, Structural Equation Modeling, Software Reliability Growth Model, Geometric Poisson Model
    Article #:  18133
Proceedings of the 18th ISSAT International Conference on Reliability and Quality in Design
July 26-28, 2012 - Boston, Massachusetts, U.S.A.