Practical duplicate bug reports detection in a large web-based development community

Most of large web-based development communities require a bug tracking system to keep track of various bug reports. However, duplicate bug reports tend to result in waste of resources, and may cause potential conflicts. There have been two types of works focusing on this problem: relevant bug report retrieval [8][11][10][13] and duplicate bug report identification [5][12]. The former methods can achieve high accuracy (82%) in the top 10 results in some dataset, but they do not really reduce the workload of developers. The latter methods still need further improvement on the performance. In this paper, we propose a practical duplicate bug reports detection method, which aims to help project team to reduce their workload by combining existing two categories of methods. We also propose some new features extracted from comments, user profiles and query feedback, which are useful for improving the detection performance. Experiments on real dataset show that our method improves the accuracy rate by 23% compared to state-of-the-art work in duplicate bug report identification, and improves the recall rate by up to 8% in relevant bug report retrieval.