Software fault prediction using BP-based crisp artificial neural networks

• Main Authors: Abaei, Golnoush, Mashinchi, M. Reza, Selamat, Ali
• Format: Article
• Language: English
• Published: Inderscience Enterprises Ltd. 2015
• Subjects: QA75 Electronic computers. Computer science
• 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
• Institution: Universiti Teknologi Malaysia

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...