Abstract. The high risk involved in the Scrum-based software development project comes from the variety of uncertainties that exist in each of its components. Therefore, the success rate needs to be predicted as a basis for the Scrum team to formulate an appropriate management strategy. This stochastic problem is represented formally in the (non-parametric) Bayesian networks model. We then design several scenarios to the generated large-scale Scrum-based development projects with multiple stakeholders and multiple feature teams. We tried to simulate several variables used in this model by using (rank nodes)-based as well as (survey and weight functions)-based algorithms. The experimental results show that the proposed model is running well so that it can be an alternative for Scrum team in predicting the success rate of the Scrum-based software development project.
Bayesian Analysis in Predicting the Success Rate of the Scrum-based Software Development Project under Stochastic Environment
Bayesian-Analysis-in-Predicting-the-Success-Rate-of-the-Scrum-based-Software-Development-Project-under-Stochastic-Environment_watermark