Enhancing software defect prediction using supervised-learning based framework. - Kamal Bashir; Tianrui Li 001; Chubato Wondaferaw Yohannese; Mahama Yahaya (ISKE, 2017)

An Empirical Study for Enhanced Software Defect Prediction Using a Learning-Based Framework. - Kamal Bashir; Tianrui Li 001; Chubato Wondaferaw Yohannese (Int. J. Comput. Intell. Syst., 2018)

A Three-Stage Based Ensemble Learning for Improved Software Fault Prediction: An Empirical Comparative Study. - Chubato Wondaferaw Yohannese; Tianrui Li 001; Kamal Bashir (Int. J. Comput. Intell. Syst., 2018)

A Hybrid Data Preprocessing Technique based on Maximum Likelihood Logistic Regression with Filtering for Enhancing Software Defect Prediction. - Kamal Bashir; Tayseer Ali; Mahama Yahaya; Ahmed Saad Hussein (ISKE, 2019)

Enhancing Crash Injury Severity Prediction on Imbalanced Crash Data by Sampling Technique with Variable Selection. - Mahama Yahaya; Xinguo Jiang; Chuanyun Fu; Kamal Bashir; Wenbo Fan (ITSC, 2019)

A-SMOTE: A New Preprocessing Approach for Highly Imbalanced Datasets by Improving SMOTE. - Ahmed Saad Hussein; Tianrui Li 001; Chubato Wondaferaw Yohannese; Kamal Bashir (Int. J. Comput. Intell. Syst., 2019)

A Novel Hybrid Approach Based on Rough Set for Classification: An Empirical Comparative Study. - Ahmed Saad Hussein; Tianrui Li 001; Chubato Wondaferaw Yohannese; Kamal Bashir (J. Multiple Valued Log. Soft Comput., 2019)

A novel feature selection method based on maximum likelihood logistic regression for imbalanced learning in software defect prediction. - Kamal Bashir; Tianrui Li 001; Mahama Yahaya (Int. Arab J. Inf. Technol., 2020)

SMOTEFRIS-INFFC: Handling the challenge of borderline and noisy examples in imbalanced learning for software defect prediction. - Kamal Bashir; Tianrui Li 001; Chubato Wondaferaw Yohannese; Mahama Yahaya (J. Intell. Fuzzy Syst., 2020)

ABL-SMOTE: A Novel Resampling Method by Handling Noisy and Borderline Challenge for Imbalanced Dataset for Software Defect Prediction. - Kamal Bashir; Sara Abdelwahab Ghorashi; Ali Ahmed 007; Abdolraheem Khader (IEEE Access, 2025)