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

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 fuzz...

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Main Authors: Abdelrafe , Elzamly, Burairah, Hussin
Format: Article
Language:English
Published: University of Zagreb 2014
Subjects:
Q Science (General)
Online Access:http://eprints.utem.edu.my/id/eprint/13113/1/2324-4122-1-PB_Jurnal_of_Computing_and_Information_Technology.pdf
http://eprints.utem.edu.my/id/eprint/13113/
http://cit.fer.hr/index.php/CIT/article/view/2324
https://doi.org/10.2498/cit.1002324
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spelling my.utem.eprints.131132023-07-31T15:48:39Z http://eprints.utem.edu.my/id/eprint/13113/ Managing software project risks (Analysis Phase) with proposed fuzzy regression analysis modelling techniques with fuzzy concepts Abdelrafe , Elzamly Burairah, Hussin Q Science (General) 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. University of Zagreb 2014 Article PeerReviewed application/pdf en cc_gnu_lgpl http://eprints.utem.edu.my/id/eprint/13113/1/2324-4122-1-PB_Jurnal_of_Computing_and_Information_Technology.pdf 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 http://cit.fer.hr/index.php/CIT/article/view/2324 https://doi.org/10.2498/cit.1002324
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
Abdelrafe , Elzamly
Burairah, Hussin
Managing software project risks (Analysis Phase) with proposed fuzzy regression analysis modelling techniques with fuzzy concepts
description 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.
format Article
author Abdelrafe , Elzamly
Burairah, Hussin
author_facet Abdelrafe , Elzamly
Burairah, Hussin
author_sort Abdelrafe , Elzamly
title Managing software project risks (Analysis Phase) with proposed fuzzy regression analysis modelling techniques with fuzzy concepts
title_short Managing software project risks (Analysis Phase) with proposed fuzzy regression analysis modelling techniques with fuzzy concepts
title_full Managing software project risks (Analysis Phase) with proposed fuzzy regression analysis modelling techniques with fuzzy concepts
title_fullStr Managing software project risks (Analysis Phase) with proposed fuzzy regression analysis modelling techniques with fuzzy concepts
title_full_unstemmed Managing software project risks (Analysis Phase) with proposed fuzzy regression analysis modelling techniques with fuzzy concepts
title_sort managing software project risks (analysis phase) with proposed fuzzy regression analysis modelling techniques with fuzzy concepts
publisher University of Zagreb
publishDate 2014
url http://eprints.utem.edu.my/id/eprint/13113/1/2324-4122-1-PB_Jurnal_of_Computing_and_Information_Technology.pdf
http://eprints.utem.edu.my/id/eprint/13113/
http://cit.fer.hr/index.php/CIT/article/view/2324
https://doi.org/10.2498/cit.1002324
_version_ 1773547661846118400
score 13.211869

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