How Good Is Genetic Programming at Predicting Changes and Defects?
One of the main problems practitioners have to deal with is the identification of change and defect proneness of source code entities (e.g., Classes). During the last years a lot of techniques have been employed for predicting change and defect proneness of classes. In this paper we study the capabi...
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| Published in: | 2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing pp. 544 - 548 |
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| Main Author: | |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
IEEE
01.09.2014
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| Subjects: | |
| ISBN: | 9781479984473, 1479984477 |
| Online Access: | Get full text |
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| Summary: | One of the main problems practitioners have to deal with is the identification of change and defect proneness of source code entities (e.g., Classes). During the last years a lot of techniques have been employed for predicting change and defect proneness of classes. In this paper we study the capabilities of Genetic Programming for performing the addressed problem by measuring the precision and recall of the obtained predictions. |
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| ISBN: | 9781479984473 1479984477 |
| DOI: | 10.1109/SYNASC.2014.78 |

