A procedure to detect problems of processes in software development projects using Bayesian networks

There are several software process models and methodologies such as waterfall, spiral and agile. Even so, the rate of successful software development projects is low. Since software is the major output of software processes, increasing software process management quality should increase the project’s chances of success. Organizations have invested to adapt software processes to their environments and the characteristics of projects to improve the productivity and quality of the products. In this paper, we present a procedure to detect problems of processes in software development projects using Bayesian networks. The procedure was successfully applied to Scrum-based software development projects. The research results should encourage the usage of Bayesian networks to manage software processes and increase the rate of successful software development projects.