DocumentCode :
2079370
Title :
Mining software engineering data
Author :
Hassan, Ahmed E. ; Xie, Tao
Author_Institution :
Queen´´s Univ., Kingston, ON, Canada
Volume :
2
fYear :
2010
fDate :
2-8 May 2010
Firstpage :
503
Lastpage :
504
Abstract :
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 have started exploring 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 data, discusses challenges associated with mining software engineering data, highlights success stories of mining software engineering data, and outlines future research directions. Attendees will acquire the knowledge and skills needed to integrate the mining of software engineering data in their own research or practice. This tutorial builds on several successful offerings at ICSE since 2007.
Keywords :
data mining; project management; software engineering; knowledge acquisition; project evolution; project progress; project status; software engineering data mining; Data mining; History; Reliability; Software engineering; Software maintenance; Tutorials; mining software engineering data; mining software repositories;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering, 2010 ACM/IEEE 32nd International Conference on
Conference_Location :
Cape Town
ISSN :
0270-5257
Print_ISBN :
978-1-60558-719-6
Type :
conf
DOI :
10.1145/1810295.1810451
Filename :
6062269
Link To Document :
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