A fuzzy logic expert system to predict module fault proneness using unlabeled data
Several techniques have been proposed to predict the fault proneness of software modules in the absence of fault data. However, the application of these techniques requires an expert assistant and is based on fixed thresholds and rules, which potentially prevents obtaining optimal prediction results...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-07-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157818300247 |