Identifying participants for collaborative merge

Software development is typically a collaborative activity. Development in large projects often involves branches, where changes are performed in parallel and merged periodically. While, there is no consensus on who should perform the merge, team members typically try to find someone with enough knowledge about the changes in the branches. This task can be difficult in cases where many different developers have made significant changes. My research proposes an approach, TIPMerge, to help select the most appropriate developers to participate in a collaborative merge session, such that we maximize the knowledge spread across changes. The goal of this research is to select a specified number of developers with the highest joint coverage. We use an optimization algorithm to find which developers form the best team together to deal with a specific merge case. We have implemented all the steps of our approach and evaluate parts of them.