Software defect prediction using deep learning-Reference-Cited by-同舟云学术

Software defect prediction using deep learning

Published:2023 Issue: Volume: Page:
ISSN:0094-243X
Container-title:ADVANCES IN INTELLIGENT APPLICATIONS AND INNOVATIVE APPROACH
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Author:

Al Faizin Achmad Iqbal,Suharto Edy,Widodo Aris Puji,Faizal Hendinur,Pratama Muhammad Naufal,Mufadhal Raihan,Azhari Rafli Azra Virendra

Publisher

AIP Publishing

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0142134

Reference5 articles.

1. Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V. and Vanderplas, J., 2011. Scikit-learn: Machine learning in Python. In Journal of Machine Learning Research, 12, pp.2825–2830.

2. Dam, H.K., Pham, T., Ng, S.W., Tran, T., Grundy, J., Ghose, A., Kim, T. and Kim, C.J., 2018. A deep tree-based model for software defect prediction. arXiv preprint arXiv:1802.00921.

3. Li, J., He, P., Zhu, J. and Lyu, M.R., 2017, July. Software defect prediction via convolutional neural network. In 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS) (pp. 318–328). IEEE.

4. Sayyad Shirabad, J., and Menzies, T.. (2005). The PROMISE Repository of Software Engineering Databases.

5. Chollet, F., and others. (2015). Keras. https://keras.io.

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