Using Document Embedding Techniques for Similar Bug Reports Recommendation

In the software development, it is common to find that several bug reports are related to many common code files, i.e., similar bugs. Similar bug recommendation is a meaningful task that could assist developers in bug triaging and fixing. If developers can focus on fewer code files, they can fix similar bugs in less time with higher quality. Therefore, building a similar bug recommendation system is a meaningful task that can improve development efficiency. As the state of the art, Yang et al.'s work presented an approach that combines TF-IDF method with Word Embedding model and achieved a good result. To further improve the performance of their approach, in this paper, we propose a novel approach using Document Embedding model. In our preliminary evaluation, we conduct the experiment on the datasets of J dt, Birt and Eclipse platform. And the results show that our approach outperforms Yang et ale ‘s, with 2.67-9.50% of improvement.