Journal of Computer Science

A COMPARISON OF STEPWISE AND FUZZY MULTIPLE REGRESSION ANALYSIS TECHNIQUES FOR MANAGING SOFTWARE PROJECT RISKS: ANALYSIS PHASE

Abdelrafe Elzamly and Burairah Hussin

DOI : 10.3844/jcssp.2014.1725.1742

Journal of Computer Science

Volume 10, Issue 9

Pages 1725-1742

Abstract

Risk is not always avoidable, but it is controllable. The aim of this study is to identify whether those techniques are effective in reducing software failure. This motivates the authors to continue the effort to enrich the managing software project risks with consider mining and quantitative approach with large data set. In this study, two new techniques are introduced namely stepwise multiple regression analysis and fuzzy multiple regression to manage the software risks. Two evaluation procedures such as MMRE and Pred (25) is used to compare the accuracy of techniques. The model’s accuracy slightly improves in stepwise multiple regression rather than fuzzy multiple regression. This study will guide software managers to apply software risk management practices with real world software development organizations and verify the effectiveness of the new techniques and approaches on a software project. The study has been conducted on a group of software project using survey questionnaire. It is hope that this will enable software managers improve their decision to increase the probability of software project success.

Copyright

© 2014 Abdelrafe Elzamly and Burairah Hussin. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.