Analysis and prediction of bug duplicates in KDE bug tracking system
Bug tracking systems (BTS) are systems that allow users of some software to report to developers bugs they encountered while using it. Common problem of BTS are duplicated reports of the same bug. Since identifying bug duplicates is a time consuming task we show in this paper an approach to automatically identifying duplicates using text-mining methods. We demonstrate the usability of our method on KDE Bugzilla BTS which contains 249,083 bug reports of which 47,093 are duplicates.