Managing Software Project Risks Using Stepwise And Fuzzy Regression Analysis Modelling Techniques

software projects have a very high failure rate. This risk of failure is not always avoidable, but it is controllable. Thus, the aim of this study is to present the stepwise and fuzzy multiple regression analysis modelling, which studies the impact of different risk management techniques and differe...

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Main Author:	Abdelrafe M.S., Elzamly
Format:	Thesis
Language:	aa aa
Published:	2016
Subjects:	Q Science (General) QA76 Computer software
Online Access:	http://eprints.utem.edu.my/id/eprint/18529/1/Managing%20Software%20Project%20Risks%20Using%20Stepwise%20And%20Fuzzy%20Regression%20Analysis%20Modelling%20Techniques%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/18529/2/Managing%20Software%20Project%20Risks%20Using%20Stepwise%20And%20Fuzzy%20Regression%20Analysis%20Modelling%20Techniques.pdf
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id	my-utem-ep.18529
record_format	uketd_dc
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	aa aa
advisor	Hussin, Burairah
topic	Q Science (General) QA76 Computer software
spellingShingle	Q Science (General) QA76 Computer software Abdelrafe M.S., Elzamly Managing Software Project Risks Using Stepwise And Fuzzy Regression Analysis Modelling Techniques
description	software projects have a very high failure rate. This risk of failure is not always avoidable, but it is controllable. Thus, the aim of this study is to present the stepwise and fuzzy multiple regression analysis modelling, which studies the impact of different risk management techniques and different software risk factors on software development projects. Furthermore, there are 5 main phases in risk management approach such as risk identification, risk analysis and evaluation, risk treatment, risk controlling, risk communication and documentation for software development life cycle. The model incorporates risk management approach and SDLC methodology to mitigate software project failure based on quantitative and intelligent risk techniques. This study provides empirical evidence for the identification of risk factors in model identify and model software risk factors and risk management techniques that effect on successful software projects. Fifty software risk factors and thirty risk management techniques were obtained from the literature to respondents. The results show that all risks in software projects are very important in the perspective of a software project manager, and all risk management techniques are the most commonly used. The study indicates that forty nine software risk factors can be mitigated by risk management techniques according to the stepwise and fuzzy multiple regression analysis modelling techniques. The model’s predictive accuracy slightly improves in fuzzy multiple regression rather than stepwise multiple regression technique. The study has been conducted on a group of software project/IT managers in Palestine. This study will guide software managers to apply software risk management practices with the real world of software development organizations. The effectiveness of the new techniques and approaches on a software project has also been verified.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Abdelrafe M.S., Elzamly
author_facet	Abdelrafe M.S., Elzamly
author_sort	Abdelrafe M.S., Elzamly
title	Managing Software Project Risks Using Stepwise And Fuzzy Regression Analysis Modelling Techniques
title_short	Managing Software Project Risks Using Stepwise And Fuzzy Regression Analysis Modelling Techniques
title_full	Managing Software Project Risks Using Stepwise And Fuzzy Regression Analysis Modelling Techniques
title_fullStr	Managing Software Project Risks Using Stepwise And Fuzzy Regression Analysis Modelling Techniques
title_full_unstemmed	Managing Software Project Risks Using Stepwise And Fuzzy Regression Analysis Modelling Techniques
title_sort	managing software project risks using stepwise and fuzzy regression analysis modelling techniques
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Information and Communication Technology
publishDate	2016
url	http://eprints.utem.edu.my/id/eprint/18529/1/Managing%20Software%20Project%20Risks%20Using%20Stepwise%20And%20Fuzzy%20Regression%20Analysis%20Modelling%20Techniques%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/18529/2/Managing%20Software%20Project%20Risks%20Using%20Stepwise%20And%20Fuzzy%20Regression%20Analysis%20Modelling%20Techniques.pdf
_version_	1747833932486803456
spelling	my-utem-ep.185292021-10-08T13:46:15Z Managing Software Project Risks Using Stepwise And Fuzzy Regression Analysis Modelling Techniques 2016 Abdelrafe M.S., Elzamly Q Science (General) QA76 Computer software software projects have a very high failure rate. This risk of failure is not always avoidable, but it is controllable. Thus, the aim of this study is to present the stepwise and fuzzy multiple regression analysis modelling, which studies the impact of different risk management techniques and different software risk factors on software development projects. Furthermore, there are 5 main phases in risk management approach such as risk identification, risk analysis and evaluation, risk treatment, risk controlling, risk communication and documentation for software development life cycle. The model incorporates risk management approach and SDLC methodology to mitigate software project failure based on quantitative and intelligent risk techniques. This study provides empirical evidence for the identification of risk factors in model identify and model software risk factors and risk management techniques that effect on successful software projects. Fifty software risk factors and thirty risk management techniques were obtained from the literature to respondents. The results show that all risks in software projects are very important in the perspective of a software project manager, and all risk management techniques are the most commonly used. The study indicates that forty nine software risk factors can be mitigated by risk management techniques according to the stepwise and fuzzy multiple regression analysis modelling techniques. The model’s predictive accuracy slightly improves in fuzzy multiple regression rather than stepwise multiple regression technique. The study has been conducted on a group of software project/IT managers in Palestine. This study will guide software managers to apply software risk management practices with the real world of software development organizations. The effectiveness of the new techniques and approaches on a software project has also been verified. UTeM 2016 Thesis http://eprints.utem.edu.my/id/eprint/18529/ http://eprints.utem.edu.my/id/eprint/18529/1/Managing%20Software%20Project%20Risks%20Using%20Stepwise%20And%20Fuzzy%20Regression%20Analysis%20Modelling%20Techniques%2024%20Pages.pdf text aa public http://eprints.utem.edu.my/id/eprint/18529/2/Managing%20Software%20Project%20Risks%20Using%20Stepwise%20And%20Fuzzy%20Regression%20Analysis%20Modelling%20Techniques.pdf text aa validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=100367 phd doctoral Universiti Teknikal Malaysia Melaka Faculty of Information and Communication Technology Hussin, Burairah 1. Aagedal, J., Braber, F., Dimitrakos, T., Gran, B., Raptis, D., and Stølen, K., 2002. 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