The Agile Software Development methodologies has enjoyed a widespread acceptance in the software development industry. While iterative and incremental approach of agile methodologies are the main attractions, at the same time they make estimation and predictability of agile software projects a challenge. Delivering workable software in short cycles helps with collecting more heuristic data as compared to traditional waterfall methodologies. Such data can be used as quantitative metrics for time and effort estimation that in turn can help with risk mitigation and risk avoidance. Although traditional agile formulations and recommendations place emphasis on individuals and interactions over processes and tools, this paper considers processes and tools essential in agile processes of today's complex software systems and distributed teams. Emphasis on processes and tools enables agile software projects to produce project metrics that can be effectively used in predictive analytics and risk management. The system that is introduced here emphasizes on quantitative approach to agile project planning and introduces a risk management model that produces risk metrics that are used to help with risk avoidance and risk mitigation. The risk metrics and the project simulation model are used to adjust project factors such as time, cost and scope during lifespan of project. Such adjustments come from recommender system that proposes changes to a wide range of project parameters for risk mitigation and risk avoidance.
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