Managing Software Project Risks (Analysis Phase) with Proposed Fuzzy Regression Analysis Modelling Techniques with Fuzzy Concepts

Abdelrafe Elzamly, Burairah Hussin


The aim of this paper is to propose 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 technique uses the fuzzy multiple regression analysis techniques 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 results show that all software risks in software projects were very important from software project manager perspective, whereas all risk management techniques are used most of the time, and often. However, these mining tests 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.


software risk management, analysis phase, software risk factors, risk management techniques, correlation analysis, fuzzy regression analysis techniques with fuzzy concepts, mining techniques, coefficient of determination

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