Wu Leon Li author Columbia University. Computer Science Columbia University. Center for Computational Learning Systems Xie Boyi author Columbia University. Computer Science Kaiser Gail E. author Columbia University. Computer Science Passonneau Rebecca author Columbia University. Computer Science Columbia University. Computer Science originator contributor text Technical reports New York Department of Computer Science, Columbia University 2011 Software bugs reported by human users and automatic error reporting software are often stored in some bug tracking tools (e.g., Bugzilla and Debbugs). These accumulated bug reports may contain valuable information that could be used to improve the quality of the bug reporting, reduce the quality assurance effort and cost, analyze software reliability, and predict future bug report trend. In this paper, we present BUGMINER, a tool that is able to derive useful information from historic bug report database using data mining, use these information to do completion check and redundancy check on a new or given bug report, and to estimate the bug report trend using statistical analysis. Our empirical studies of the tool using several real-world bug report repositories show that it is effective, easy to implement, and has relatively high accuracy despite low quality data. Computer science CUCS-024-11 http://hdl.handle.net/10022/AC:P:13132 English NNC NNC 2012-05-03 16:25:02 -0400 2012-05-03 16:31:47 -0400 7135 eng