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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Adams, B. Zhen Ming Jiang Hassan, A.E. |
| Copyright Year | 2010 |
| Description | Author affiliation: Queen's University, Canada (Adams, B.; Zhen Ming Jiang; Hassan, A.E.) |
| Abstract | Detailed knowledge about implemented concerns in the source code is crucial for the cost-effective maintenance and successful evolution of large systems. Concern mining techniques can automatically suggest sets of related code fragments that likely contribute to the implementation of a concern. However, developers must then spend considerable time understanding and expanding these concern seeds to obtain the full concern implementation. We propose a new mining technique (COMMIT) that reduces this manual effort. COMMIT addresses three major shortcomings of current concern mining techniques: 1) their inability to merge seeds with small variations, 2) their tendency to ignore important facets of concerns, and 3) their lack of information about the relations between seeds. A comparative case study on two large open source C systems (Post-greSQL and NetBSD) shows that COMMIT recovers up to 87.5% more unique concerns than two leading concern mining techniques, and that the three techniques complement each other. |
| Starting Page | 305 |
| Ending Page | 314 |
| File Size | 310272 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781605587196 |
| ISSN | 02705257 |
| DOI | 10.1145/1806799.1806846 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-05-02 |
| Publisher Place | South Africa |
| Access Restriction | Subscribed |
| Rights Holder | Association for Computing Machinery, Inc. (ACM) |
| Subject Keyword | Data mining Mutual information Scattering Synchronization Servers Maintenance engineering Software mining software repositories concern mining empirical research |
| Content Type | Text |
| Resource Type | Article |
| Subject | Software |
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