Multi-agent Simulation of Agile Team Dynamics: Experiments on Team Strategies Comparisons

Abstract

Scrum is an agile process that incrementally, iteratively and continuously delivers software based on sprints. It is comprised of user stories stored in product backlogs and delivered through sprints by a Scrum team consisting of developers, a Scrum Master and a Product Owner. The performance of a Scrum team is largely dependent on the capabilities of team members and the technical practices they adopt. One such practice, pair programming has been studied in a variety of contexts but not extensively in a Scrum context. Pair programming is a technique where two programmers work side by side to design, code, and test their program. A multi agent system is used to simulate a scrum environment where a team (with varying team members’ capability) work on delivering user stories (which consists of multiple tasks with varying complexities) in multiple sprints. Using this simulated environment, various strategies of compulsory pairing and voluntary pairing are investigated. Impact is measured based on the team’s work efficiency, completion time, effort time and idle time. Experiments were performed to test these strategies in varying environments and results showed that a hybrid pairing strategy performed the best in fixed environments as it avoided negative pairing situations. An adaptive strategy (which changes strategy depending of the composition of the team and the tasks to be completed) performed best in the random setting as it was able to use the best strategy based on the current environment.