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http://dx.doi.org/10.7236/JIIBC.2022.22.4.111

Prediction Model of Software Fault using Deep Learning Methods  

Hong, Euyseok (Dept. of Computer Engineering, Sungshin Women's University)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.22, no.4, 2022 , pp. 111-117 More about this Journal
Abstract
Many studies have been conducted on software fault prediction models for decades, and the models using machine learning techniques showed the best performance. Deep learning techniques have become the most popular in the field of machine learning, but few studies have used them as classifiers for fault prediction models. Some studies have used deep learning to obtain semantic information from the model input source code or syntactic data. In this paper, we produced several models by changing the model structure and hyperparameters using MLP with three or more hidden layers. As a result of the model evaluation experiment, the MLP-based deep learning models showed similar performance to the existing models in terms of Accuracy, but significantly better in AUC. It also outperformed another deep learning model, the CNN model.
Keywords
Fault prediction; Deep learning; Machine learning;
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Times Cited By KSCI : 2  (Citation Analysis)
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