Using Bayesian Belief Networks to Model Software Project Management Antipatterns

Abstract

In spite of numerous traditional and agile software project management models proposed, process and project modeling still remains an open issue. This paper proposes a Bayesian Network (BN) approach for modeling software project management antipatterns. This approach provides a framework for project managers, who would like to model the cause-effect relationships that underlie an antipattern, taking into account the inherent uncertainty of a software project. The approach is exemplified through a specific BN model of an antipattern. The antipattern is modeled using the empirical results of a controlled experiment on Extreme Programming (XP) that investigated the impact of developer personalities and temperaments on communication, collaboration-pair viability and effectiveness in pair programming. The resulting BN model provides the precise mathematical model of a project management antipattern and can be used to measure and handle uncertainty in mathematical terms.