Integrated approach to software defect prediction EA Felix, SP Lee IEEE Access 5, 21524-21547, 2017 | 75 | 2017 |
Systematic literature review of preprocessing techniques for imbalanced data EA Felix, SP Lee Iet Software 13 (6), 479-496, 2019 | 59 | 2019 |
Predicting the number of defects in a new software version EA Felix, SP Lee PloS one 15 (3), e0229131, 2020 | 29 | 2020 |
A systematic review on search‐based test suite reduction: State‐of‐the‐art, taxonomy, and future directions AS Habib, SUR Khan, EA Felix IET Software 17 (2), 93-136, 2023 | 6 | 2023 |
Prevalence of machine learning techniques in software defect prediction MF Sohan, MA Kabir, M Rahman, T Bhuiyan, MI Jabiullah, EA Felix Cyber Security and Computer Science: Second EAI International Conference …, 2020 | 5 | 2020 |
Predicting the number of COVID-19 infections and deaths in USA AF Ebubeogu, CE Ozigbu, K Maswadi, A Seixas, P Ofem, DF Conserve Globalization and health 18 (1), 37, 2022 | 3 | 2022 |
Impact of defect velocity at class level EA Felix, SP Lee 2017 International Conference on Robotics and Automation Sciences (ICRAS …, 2017 | 2 | 2017 |
A research landscape on software defect prediction A Taskeen, SUR Khan, EA Felix Journal of Software: Evolution and Process 35 (12), e2549, 2023 | | 2023 |
Prevalence of Machine Learning Techniques in Software Defect Prediction T Bhuiyan, MI Jabiullah, EA Felix Cyber Security and Computer Science: Second EAI International Conference …, 2020 | | 2020 |
Supervised Optimal Decision Machine Learning Approach to Class-and Method-level Data Preprocessing Towards Effective Software Defect Prediction EA Felix PQDT-Global, 2020 | | 2020 |
Robot System Design and Control T Sasaki, S Yamada | | |