Published January 1, 2010
| Version v1
Journal article
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Defect prediction from static code features: current results, limitations, new approaches
- 1. W Virginia Univ, Morgantown, WV 26506 USA
- 2. Univ Oulu, Oulu, Finland
- 3. Bogazici Univ, Istandbul, Turkey
Description
Building quality software is expensive and software quality assurance (QA) budgets are limited. Data miners can learn defect predictors from static code features which can be used to control QA resources; e.g. to focus on the parts of the code predicted to be more defective.
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