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Managing Software Project Risk With Proposed Regression Model Techniques and Effect Size Technique

Regardless how much effort we put for the success of software projects, many software projects have very high failure rate and risks are everywhere in life and most assuredly during the life of software projects. Risk is not always avoidable, but it is controllable. The aim of this paper is to prese...

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Main Authors: Hussin, B., Abdelrafe, E.
Format: Article
Language:English
Published: Praise Worthy Prize 2011
Subjects:
Q Science (General)
Online Access:http://eprints.utem.edu.my/id/eprint/95/1/Managing_Software_Project_Resik_with_Proposed_Regressiion_Model_Techniques_and_Effect_Size_Technique.pdf
http://eprints.utem.edu.my/id/eprint/95/
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spelling my.utem.eprints.952021-09-19T22:31:24Z http://eprints.utem.edu.my/id/eprint/95/ Managing Software Project Risk With Proposed Regression Model Techniques and Effect Size Technique Hussin, B. Abdelrafe, E. Q Science (General) Regardless how much effort we put for the success of software projects, many software projects have very high failure rate and risks are everywhere in life and most assuredly during the life of software projects. Risk is not always avoidable, but it is controllable. The aim of this paper is to present new techniques by which we can study the impact of different control factors and different risk factors on software projects risk and we knew how to deliver good quality solutions. The new technique uses the regression test and effect size test proposed to managing the risks in a software project and reducing risk with software process improvement. Fourteen risk factors and eighteen control factors were used in this paper. The nine of fourteen factors mitigated by using control factors. The study has been conducted on a group of managers. Successful project risk management will greatly improve the probability of project success. Praise Worthy Prize 2011 Article NonPeerReviewed text en http://eprints.utem.edu.my/id/eprint/95/1/Managing_Software_Project_Resik_with_Proposed_Regressiion_Model_Techniques_and_Effect_Size_Technique.pdf Hussin, B. and Abdelrafe, E. (2011) Managing Software Project Risk With Proposed Regression Model Techniques and Effect Size Technique. International Review on Computers and Software (IRECOS) , 6 (N. 2). pp. 250-263. ISSN 1828-6003
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)
Hussin, B.
Abdelrafe, E.
Managing Software Project Risk With Proposed Regression Model Techniques and Effect Size Technique
description Regardless how much effort we put for the success of software projects, many software projects have very high failure rate and risks are everywhere in life and most assuredly during the life of software projects. Risk is not always avoidable, but it is controllable. The aim of this paper is to present new techniques by which we can study the impact of different control factors and different risk factors on software projects risk and we knew how to deliver good quality solutions. The new technique uses the regression test and effect size test proposed to managing the risks in a software project and reducing risk with software process improvement. Fourteen risk factors and eighteen control factors were used in this paper. The nine of fourteen factors mitigated by using control factors. The study has been conducted on a group of managers. Successful project risk management will greatly improve the probability of project success.
format Article
author Hussin, B.
Abdelrafe, E.
author_facet Hussin, B.
Abdelrafe, E.
author_sort Hussin, B.
title Managing Software Project Risk With Proposed Regression Model Techniques and Effect Size Technique
title_short Managing Software Project Risk With Proposed Regression Model Techniques and Effect Size Technique
title_full Managing Software Project Risk With Proposed Regression Model Techniques and Effect Size Technique
title_fullStr Managing Software Project Risk With Proposed Regression Model Techniques and Effect Size Technique
title_full_unstemmed Managing Software Project Risk With Proposed Regression Model Techniques and Effect Size Technique
title_sort managing software project risk with proposed regression model techniques and effect size technique
publisher Praise Worthy Prize
publishDate 2011
url http://eprints.utem.edu.my/id/eprint/95/1/Managing_Software_Project_Resik_with_Proposed_Regressiion_Model_Techniques_and_Effect_Size_Technique.pdf
http://eprints.utem.edu.my/id/eprint/95/
_version_ 1712288900875026432
score 13.211869

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