Automatic Bug Assignment Using Information Extraction Methods

Abstract

The number of reported bugs in large open source projects is high and triaging these bugs is an important issue in software maintenance. As a step in the bug triaging process, assigning a new bug to the most appropriate developer to fix it, is not only a time-consuming and tedious task. The triager, the person who considers a bug and assigns it to a developer, also needs to be aware of developer activities at different parts of the project. It is clear that only a few developers have this ability to carry out this step of bug triaging. The main goal of this paper is to suggest a new approach to the process of performing automatic bug assignment. The information needed to select the best developers to fix a new bug report is extracted from the version control repository of the project. Unlike all the previous suggested approaches which used Machine Learning and Information Retrieval methods, this research employs the Information Extraction (IE) methods to extract the information from the software repositories. The proposed approach does not use the information of the bug repository to make decisions about bugs in order to obtain better results on projects which do not have many fixed bugs. The aim of this research is to recommend the actual fixers of the bugs. Using this approach, we achieved 62%, 43% and 41% accuracies on Eclipse, Mozilla and Gnome projects, respectively.