Software fault prediction using BP-based crisp artificial neural networks
Early fault detection for software reduces the cost of developments. Fault level can be predicted through learning mechanisms. Conventionally, precise metrics measure the fault level and crisp artificial neural networks (CANNs) perform the learning. However, the performance of CANNs depends on compl...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Inderscience Enterprises Ltd.
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/56016/1/GolnoushAbaei2015_SoftwareFaultPredictionUsingBPBasedCrisp.pdf http://eprints.utm.my/id/eprint/56016/ http://dx.doi.org/10.1504/IJIIDS.2015.070825 |
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| Institution: | Universiti Teknologi Malaysia |
| Language: | English |