Balanced Adversarial Tight Matching for Cross-Project Defect Prediction
Cross-project defect prediction (CPDP) is an attractive research area in software testing. It identifies defects in projects with limited labeled data (target projects) by utilizing predictive models from data-rich projects (source projects). Existing CPDP methods based on transfer learning mainly r...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
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| Series: | IET Software |
| Online Access: | http://dx.doi.org/10.1049/2024/1561351 |
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