ITERATION SCHEDULING USING BAYESIAN NETWORKS IN AGILE SOFTWARE DEVELOPMENT

Abstract

In software industry nowadays, Agile Software Development methods have been largely adopted. Agile Software Development methods themselves can be considered a certain level of reducing projects risks. However, optimization of software project scheduling has always been big challenges in both practice and academia, since industrial software development is a highly complex and dynamic process. There is also a need for a probabilistic method that better model and predict uncertainty in software projects. This paper proposes an enhanced method and algorithm by combining optimized agile iteration scheduling and the ability to predict and handle risks in resource-constrained contexts of Bayesian Networks. Based on the method, a software was developed as a support tool for managers to control their project schedules. The tool also provides a reliable set of strategies of sequencing tasks in agile iteration scheduling.