Forecasting Communication Behavior in Student Software Projects

Communication is an essential part of software product development. Therefore, communication is an inevitable means for information sharing. For example, ill-communicated requirements, guidelines or decisions complicate working in a team and may threaten project success. Hence, monitoring communication behavior can help fostering project success by preventing loss of information due to insufficient communication. Knowledge about a team's communication behavior and information sharing enables the corresponding project leader to react. Forecasting communication behavior can indicate critical situations like too little communication, inappropriate media or wrong receivers at early project stages. A good forecast can identify if there is a need to change communication behavior. In a study with 165 students in 34 teams participating in a software project, we collected data concerning the used communication channels and perceived intensity. We combine these two parameters for analyzing and forecasting communication behavior. Considering the displayed evolution of communication behavior within a team can indicate the necessity to intervene. For example, the project leader can establish one more meeting each week to support information exchange. Our forecasting algorithm bases on k-nearest neighbor selection in order to identify comparable projects. We validate this approach using cross validation, which leads to an average accuracy of 90%. This level of accuracy may provide a reliable forecast and a good opportunity for early conflict identification.