Mining Software Engineering Data

Authors:
Tao Xie;Jian Pei;Ahmed E. Hassan
Affiliations:
North Carolina State Univ., USA;Simon Fraser Univ., Canada;Univ. of Victoria, Canada
Venue:
ICSE COMPANION '07 Companion to the proceedings of the 29th International Conference on Software Engineering
Year:
2007

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Abstract

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.