Managing software project risks (Analysis Phase) with proposed fuzzy regression analysis modelling techniques with fuzzy concepts

Abdelrafe , Elzamly and Burairah, Hussin (2014) Managing software project risks (Analysis Phase) with proposed fuzzy regression analysis modelling techniques with fuzzy concepts. Journal of Computing and Information Technology, 22 (2). pp. 131-144. ISSN 1330-1136

PDF 2324-4122-1-PB_Jurnal_of_Computing_and_Information_Technology.pdf - Published Version Restricted to Registered users only Available under License Creative Commons GNU LGPL (Software). Download (223kB)

Abstract

The aim of this paper is to proposed new mining techniques by which we can study the impact of different risk management techniques and different software risk factors on software analysis development projects. The new mining techniques uses the fuzzy multiple regression analysis technique with fuzzy concepts to manage the software risks in a software project and mitigating risk with software process improvement. Top ten software risk factors in analysis phase and thirty risk management techniques were presented to respondents. The result show that all software risks in software project were very important from software project manager perspective, whereas all risk management techniques are used most of the time and often. However, these mining test were performed using fuzzy multiple regression analysis techniques to compare the risk management techniques with each of the software risk factors to determine if they are effective in reducing the occurrence of each software risk factor. The study has been conducted on a group of software project managers. Successful software project risk management will greatly improve the probability of software project success.

Item Type:	Article
Uncontrolled Keywords:	software risk management, analysis phase, software risk factors, risk management techniques, cor�relation analysis, fuzzy regression analysis techniques with fuzzy concepts, mining techniques, coefficient of determination
Subjects:	Q Science > Q Science (General)
Divisions:	Faculty of Information and Communication Technology > Department of Industrial Computing
Depositing User:	Users 3 not found.
Date Deposited:	15 Aug 2014 11:54
Last Modified:	31 Jul 2023 15:48
URI:	http://eprints.utem.edu.my/id/eprint/13113
Statistic Details:	View Download Statistic

Actions (login required)

View Item