OPTIMIZATION OF SOFTWARE DEFECT PREDICTION USING CNN AND ADABOOST: ANALYSIS AND EVALUATION
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Begum, M., Shuvo, M.H., Nasir, M.K., Hossain, A., Hossain, M.J., Ashraf, I., Uddin, J., Samad, M.A., “LCNN: Lightweight CNN Archi-tecture for Software Defect Feature Identification Using Explainable AI,” IEEE Access, vol. 2024, no. 1, pp. 123-134, 2024.
Nasraldeen Alnor Adam Khleel, Károly Nehéz, “A Novel Approach for SDP Using CNN and GRU Based on SMOTE Tomek Method,” IEEE Access, vol. 2023, pp. 1-10, 2023.
Ramakrishna, M.T., Venkatesan, V.K., Izonin, I., Havryliuk, M., Bhat, C.R., “Homogeneous Adaboost Ensemble Machine Learning Algo-rithms with Reduced Entropy on Balanced Data,” Entropy, vol. 25, no. 2, pp. 245, 2023.
Ogunsanya, M., Isichei, D., Desai, M., “Grid Search Hyperparameter Tuning in Additive Manufacturing Processes,” Journal of Manufac-turing Processes, vol. 2023, no. 3, pp. 432-445, 2023.
Hornyák, O., Iantovics, L.B., “AdaBoost Algorithm Could Lead to Weak Results for Data with Certain Characteristics,” Entropy, vol. 2023, no. 5, pp. 789-800, 2023.
Giray, G., et al., “On the Use of Deep Learning in SDP,” Journal of Systems and Software, vol. 2023, no. 8, pp. 123-135, 2023.
Pachouly, J., et al., “A Systematic Literature Review on SDP Using Artificial Intelligence: Datasets, Data Validation Methods, Approaches, and Tools,” Information and Software Technology, vol. 2022, no. 7, pp. 567-579, 2022.
Chen, L.-q., et al., “SDP Based on Nested-Stacking and Heterogeneous Feature Selection,” Expert Systems with Applications, vol. 2022, no. 9, pp. 345-356, 2022.
Uddin, M.N., Li, B., Ali, Z., Kefalas, P., Khan, I., Zada, I., “SDP Employing BiLSTM and BERT-based Semantic Feature,” Soft Compu-ting, vol. 2022, no. 7, pp. 1234-1245, 2022.
Alazba, A., Aljamaan, H., “SDP Using Stacking Generalization of Optimized Tree-Based Ensembles,” Applied Sciences, vol. 12, no. 9, pp. 4577, 2022.