Managing Software Project Risk With Proposed Regression Model Techniques and Effect Size Technique - Hussin, B.; Abdelrafe, E. (Praise Worthy Prize, 2011)
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.