Needfeed: Taming change notifications by modeling code relevance

Abstract

Most software development tools allow developers to subscribe to notifications about code checked-in by their team members in order to review changes to artifacts that they are responsible for. However, past user studies have indicated that this mechanism is counter-productive, as developers spend a significant amount of effort sifting through such feeds looking for items that are relevant to them. We present NeedFeed, a system that models code relevance by mining a project's software repository and highlights changes that a developer may need to review. We evaluate several techniques to model code relevance, from a naive TOUCH-based approach to generic HISTORY-based classifiers using temporal code metrics at file and method-level granularities, which are then improved by building developer-specific models using TEXT-based features from commit messages. NeedFeed reduces notification clutter by more than 90%, on average, with the best strategy giving an average precision and recall of more than 75%.