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Analysis and prediction of bug duplicates in KDE bug tracking system

This video was recorded at Slovenian KDD Conference on Data Mining and Data Warehouses (SiKDD), Ljubljana 2011. 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.

Keywords:: videolectures, ocwc, oec

Disciplines:

Science and Technology / Computer Science

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Material Type:: Presentation
Date Added to MERLOT:: February 10, 2015
Date Modified in MERLOT:: February 10, 2015
Author:: Gregor Leban, Faculty of Computer and Information Science, University of Ljubljana
Submitter:: The Open Education Consortium
Primary Audience:: College General Ed, College Lower Division, College Upper Division
Technical Format:: Video

Mobile Compatibility:: Not specified at this time
Language:: English
Cost Involved:: No
Source Code Available:: No
Accessibility Information Available:: Unknown
Creative Commons:: This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States