Using Data Mining Techniques to Improve Software Reliability
Li, Zhenmin
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/81753
Description
Title
Using Data Mining Techniques to Improve Software Reliability
Author(s)
Li, Zhenmin
Issue Date
2006
Doctoral Committee Chair(s)
Zhou, Yuanyuan
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
Copy-pasted code is very common in large software, but it is prone to introducing bugs. CP-Miner uses frequent sequence mining to efficiently identify copy-pasted code in large software, and detects copy-paste related bugs. In order to further understand copy-paste in system software, this dissertation also analyzes some interesting characteristics of copy-paste in Linux and FreeBSD.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.