Mining software engineering data

Tao Xie, Jian Pei, Ahmed E. Hassan

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Software engineering data (such as code bases, execution traces, historical code changes, mailing lists, and bug databases) contains a wealth of information about a project's status, progress, and evolution. Using well-established data mining techniques, practitioners and researchers can explore the potential of this valuable data in order to better manage their projects and to produce higher-quality software systems that are delivered on time and within budget. This tutorial presents the latest research in mining Software Engineering (SE) data, discusses challenges associated with mining SE data, highlights SE data mining success stories, and outlines future research directions. Participants will acquire knowledge and skills needed to perform research or conduct practice in the field and to integrate data mining techniques in their own research or practice.

Original languageEnglish (US)
Title of host publicationProceedings - 29th International Conference on Software Engineering, ICSE 2007; Companion Volume
Number of pages2
StatePublished - 2007
Externally publishedYes
Event29th International Conference on Software Engineering, ICSE 2007 - Minneapolis, MN, United States
Duration: May 20 2007May 26 2007

Publication series

NameProceedings - International Conference on Software Engineering
ISSN (Print)0270-5257


Other29th International Conference on Software Engineering, ICSE 2007
Country/TerritoryUnited States
CityMinneapolis, MN

ASJC Scopus subject areas

  • Software


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