Recommending frequently encountered bugs.

Developers introduce bugs during software development which reduce software reliability. Many of these bugs are commonly occurring and have been experienced by many other developers. Informing developers, especially novice ones, about commonly occurring bugs in a domain of interest (e.g., Java), can help developers comprehend program and avoid similar bugs in the future. Unfortunately, information about commonly occurring bugs are not readily available. To address this need, we propose a novel approach named RFEB which recommends frequently encountered bugs (FEBugs) that may affect many other developers. RFEB analyzes Stack Overflow which is the largest software engineering-specific Q&A communities. Among the plenty of questions posted in Stack Overflow, many of them provide the descriptions and solutions of different kinds of bugs. Unfortunately, the search engine that comes with Stack Overflow is not able to identify FEBugs well. To address the limitation of the search engine of Stack Overflow, we propose RFEB which is an integrated and iterative approach that considers both relevance and popularity of Stack Overflow questions to identify FEBugs. To evaluate the performance of RFEB, we perform experiments on a dataset from Stack Overflow which contains more than ten million posts. We compared our model with Stack Overflow's search engine on 10 domains, and the experiment results show that RFEB achieves the average NDCG10 score of 0.96, which improves Stack Overflow's search engine by 20%.