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29th International Conference on Software Engineering (ICSE'07 Companion)
Minneapolis, Minnesota
May 20-May 26
ISBN: 0-7695-2892-9
Tao Xie, North Carolina State Univ., USA
Jian Pei, Simon Fraser Univ., Canada
Ahmed E. Hassan, Univ. of Victoria, Canada
Software engineering data (such as code bases, exe- cution 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 re- searchers 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 Soft- ware Engineering (SE) data, discusses challenges associ- ated with mining SE data, highlights SE data mining suc- cess stories, and outlines future research directions. Partic- ipants 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.

Citation:
Tao Xie, Jian Pei, Ahmed E. Hassan, "Mining Software Engineering Data," icsecompanion, pp.172-173, 29th International Conference on Software Engineering (ICSE'07 Companion), 2007
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