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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| Format: | Thesis |
| Language: | aa aa |
| Published: |
2016
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| 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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| Summary: | 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. |
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