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Identifying crosscutting concerns using historical code changes
| Content Provider | CiteSeerX |
|---|---|
| Author | Adams, Bram Ming, Zhen Ahmed, Jiang Hassan, E. |
| Description | 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 (PostgreSQL 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. |
| File Format | |
| Language | English |
| Publisher Institution | 32nd International Conference on Software Engineering (Cape Town, South Africa |
| Access Restriction | Open |
| Subject Keyword | Full Concern Implementation Considerable Time Understanding Source Code Important Facet Comparative Case Study Concern Mining Technique Manual Effort Historical Code Change Unique Concern New Mining Technique Related Code Fragment Current Concern Mining Technique Large System Successful Evolution Large Open Source System Concern Seed Small Variation Major Shortcoming Cost-effective Maintenance |
| Content Type | Text |
| Resource Type | Article |
