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Software risk management plays a vital role in successful software project management. In fact, all the phases of the software development life cycle (SDLC) are potential sources of software risks since it involves hardware, software, technology, people, cost, and schedule. There are a number of software risk factors that affect the whole software development process. However, finding the correlation between risk factors and project outcome is the main focus of present research on software risk analysis. In this paper, a probabilistic software risk estimation model is proposed using Bayesian Belief Network (BBN) that focuses on the top software risk indicators for risk assessment in software development projects. In order to assess the constructed model, an empirical experiment has been performed, based on the data collected from software development projects used by an organization.
Kumar et al. (Thu,) studied this question.
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