NDLI: Learning to Rank Relevant Files for Bug Reports using Domain Knowledge

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Learning to Rank Relevant Files for Bug Reports using Domain Knowledge

Content Provider	CiteSeerX
Author	Ye, Xin Bunescu, Razvan Liu, Chang
Abstract	When a new bug report is received, developers usually need to reproduce the bug and perform code reviews to nd the cause, a process that can be tedious and time consuming. A tool for ranking all the source les of a project with respect to how likely they are to contain the cause of the bug would enable developers to narrow down their search and poten-tially could lead to a substantial increase in productivity. This paper introduces an adaptive ranking approach that leverages domain knowledge through functional decomposi-tions of source code les into methods, API descriptions of library components used in the code, the bug-xing history, and the code change history. Given a bug report, the ranking score of each source le is computed as a weighted combi-nation of an array of features encoding domain knowledge, where the weights are trained automatically on previously solved bug reports using a learning-to-rank technique. We evaluated our system on six large scale open source Java projects, using the before-x version of the project for every bug report. The experimental results show that the newly introduced learning-to-rank approach signicantly outper-forms two recent state-of-the-art methods in recommending relevant les for bug reports. In particular, our method makes correct recommendations within the top 10 ranked source les for over 70 % of the bug reports in the Eclipse Platform and Tomcat projects.
File Format	PDF
Access Restriction	Open
Subject Keyword	Bug Report Domain Knowledge Source Le Rank Relevant File Learning-to-rank Approach Ranking Score Functional Decomposi-tions Bug-xing History Recent State-of-the-art Method Adaptive Ranking Approach Api Description Code Review Source Code Learning-to-rank Technique Library Component Correct Recommendation Time Consuming Substantial Increase Weighted Combi-nation New Bug Report Before-x Version Relevant Le Eclipse Platform Code Change History Tomcat Project Experimental Result
Content Type	Text
Resource Type	Article

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