A Framework to Build Bayesian Networks to Assess Scrum-based Software Development Methods

Agile software development has been increasingly used to satisfy the need to respond to fast moving market demand and gain market share. Scrum, which is a project management framework, dominates as the most popular agile method. In the literature, there are a number of solutions to customize and assess Scrum-based agile methods, but they are limited to focus only on process factors, assume a predefined set of practices or rely only on subjective evaluation. This paper presents a framework to build a Bayesian Network to assist on the assessment of Scrum-based software development methods. The BN models the main entities of the software development process and can be complemented with software practices and metrics. To evaluate the completeness of our solution, we performed simulations to check if the proposed framework diagnoses 14 known Scrum anti-patterns extracted from the literature. 12 antipatterns were directly detected, 1 was indirectly detected by the BN and 1 was considered as invalid. We concluded that the proposed solution is complete to detect the major flaws of Scrum-based software development methods and can be used to assist on the configuration, adoption and continuous improvement of Scrum teams.