Analysis and prediction of bug duplicates in KDE bug tracking system

author: Gregor Leban, Artificial Intelligence Laboratory, Jožef Stefan Institute
published: Nov. 4, 2011,   recorded: October 2011,   views: 104
Categories

Slides

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

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.

See Also:

Download slides icon Download slides: sikdd2011_leban_duplicates_01.pdf (592.3 KB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: