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| Content Provider | ACM Digital Library |
|---|---|
| Author | Ingram, Claire Riddle, Steve |
| Abstract | One technique from value-based software engineering involves prioritising the system and selectively applying time-consuming techniques (such as traceability) in order to maximise return on investment. This prioritisation could be based on predicted change-proneness of code modules, if a sufficiently accurate prediction can be achieved. Several previous studies have examined links between software change-proneness and software metrics such as size and complexity. However, conclusions differ as to the strength of the relationships. We present here a new case study project, extracting a range of complexity values from the code modules and testing for the existence of a significant link between change-proneness and complexity. We find only limited evidence of a linear relationship, but analysis using other statistical techniques does reveal some other significant links. |
| Starting Page | 31 |
| Ending Page | 37 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781450305938 |
| DOI | 10.1145/1985374.1985384 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2011-05-24 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Software metrics Volatility Software size Design metrics Change-proneness Value-based software engineering |
| Content Type | Text |
| Resource Type | Article |
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