Two mathematical modeling approaches for extreme programming

Software development investments are always seeking low risk software development processes. Extreme programming (XP) is one of the most popular agile methodologies. Currently, increasing numbers of software companies depend on XP. This research is an attempt to build two mathematical modeling approaches in order to present and describe XP. It compares between their inputs and outputs to comprehend the best approach. The approaches are based on two white boxes and one black box. The first modeling approach uses a set of critical success factors and another set of user defined weights to calculate the project success rate (SR). The second modeling approach uses a modified set of critical success factors with another approach; expecting unknown factors and weights. Those models describe the real development environment as the work is based on real data from two projects. The data is used to test the models. As a result, the two approaches are evaluated, verified and enhanced to form a model that calculates the SR and success radio for projects. At the end of this research, one of the two models is preferred due to its dependability and reliability.