Assisting the continuous improvement ofScrumprojects using metrics and Bayesian networks
Mirko Perkusich, Kyller Gorgônio, Hyggo Oliveira de Almeida, Ângelo Perkusich · Journal of Software Evolution and Process · 2016
Abstract Scrumis a simple process to understand, but hard to adopt. Therefore, there is a need for resources to assist on its adoption. In this paper, we present the process followed to build aBayesian networkto assist on the assessment of the quality of the software process in the context ofScrumprojects. The model provides data to helpScrum Masterslead the improvement of business value delivery ofScrumteams. The process is divided into 2 phases. In the first phase, we built theBayesian networkbased on expert knowledge extracted from the literature and experts. We used a top‐down approach and reasoning to define the key metrics necessary to build the models and their relationships. In the second phase, we updated theBayesian networkbased on limitations of the first version. We validated theBayesian networkinferences with 10 simulated scenarios. Comparing both versions, for all scenarios, we improved the accuracy of the inferences. Therefore, we concluded that theBayesian networksadequately representScrumprojects from the viewpoint of theScrumMaster. Finally, the model built is in conformance with agile methods tailoring and can be adapted to anyScrumteam.