Research Article Open Access

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

Abdelrafe Elzamly1 and Burairah Hussin2
  • 1 Universiti Teknikal Malaysia Melaka (UTeM), Malaysia
  • 2 Al-Aqsa University, Palestinian Authority

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.

Journal of Computer Science
Volume 10 No. 9, 2014, 1725-1742

DOI: https://doi.org/10.3844/jcssp.2014.1725.1742

Submitted On: 18 January 2014 Published On: 22 April 2014

How to Cite: Elzamly, A. & Hussin, B. (2014). A COMPARISON OF STEPWISE AND FUZZY MULTIPLE REGRESSION ANALYSIS TECHNIQUES FOR MANAGING SOFTWARE PROJECT RISKS: ANALYSIS PHASE. Journal of Computer Science, 10(9), 1725-1742. https://doi.org/10.3844/jcssp.2014.1725.1742

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Keywords

  • Software Project Management
  • Software Risk Management
  • Software Risk Factors
  • Risk Management Technique
  • Stepwise Regression Analysis Techniques
  • Fuzzy Multiple Regression Analysis
  • Analysis Phase