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Kwabena Ebo Bennin
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Mahakil: Diversity based oversampling approach to alleviate the class imbalance issue in software defect prediction
KE Bennin, J Keung, P Phannachitta, A Monden, S Mensah
IEEE Transactions on Software Engineering 44 (6), 534-550, 2017
3412017
Improving bug localization with word embedding and enhanced convolutional neural networks
Y Xiao, J Keung, KE Bennin, Q Mi
Information and Software Technology 105, 17-29, 2019
1212019
COSTE: Complexity-based OverSampling TEchnique to alleviate the class imbalance problem in software defect prediction
S Feng, J Keung, X Yu, Y Xiao, KE Bennin, MA Kabir, M Zhang
Information and Software Technology 129, 106432, 2021
1192021
On the use of deep learning in software defect prediction
G Giray, KE Bennin, Ö Köksal, Ö Babur, B Tekinerdogan
Journal of Systems and Software 195, 111537, 2023
1132023
On the relative value of data resampling approaches for software defect prediction
KE Bennin, JW Keung, A Monden
Empirical Software Engineering 24, 602-636, 2019
912019
Improving bug localization with an enhanced convolutional neural network
Y Xiao, J Keung, Q Mi, KE Bennin
2017 24th Asia-Pacific Software Engineering Conference (APSEC), 338-347, 2017
692017
Empirical evaluation of cross-release effort-aware defect prediction models
KE Bennin, K Toda, Y Kamei, J Keung, A Monden, N Ubayashi
2016 IEEE international conference on software quality, reliability and …, 2016
652016
Cross project defect prediction using class distribution estimation and oversampling
N Limsettho, KE Bennin, JW Keung, H Hata, K Matsumoto
Information and Software Technology 100, 87-102, 2018
632018
Machine translation-based bug localization technique for bridging lexical gap
Y Xiao, J Keung, KE Bennin, Q Mi
Information and Software Technology 99, 58-61, 2018
552018
Improving ranking-oriented defect prediction using a cost-sensitive ranking SVM
X Yu, J Liu, JW Keung, Q Li, KE Bennin, Z Xu, J Wang, X Cui
IEEE Transactions on Reliability 69 (1), 139-153, 2019
542019
Investigating the effects of balanced training and testing datasets on effort-aware fault prediction models
KE Bennin, J Keung, A Monden, Y Kamei, N Ubayashi
2016 IEEE 40th annual Computer software and applications conference (COMPSAC …, 2016
522016
Cross-company defect prediction via semi-supervised clustering-based data filtering and MSTrA-based transfer learning
X Yu, M Wu, Y Jian, KE Bennin, M Fu, C Ma
Soft Computing 22, 3461-3472, 2018
502018
An empirical study of learning to rank techniques for effort-aware defect prediction
X Yu, KE Bennin, J Liu, JW Keung, X Yin, Z Xu
2019 IEEE 26th International Conference on Software Analysis, Evolution and …, 2019
492019
Comparing learning to rank techniques in hybrid bug localization
Z Shi, J Keung, KE Bennin, X Zhang
Applied Soft Computing 62, 636-648, 2018
492018
The significant effects of data sampling approaches on software defect prioritization and classification
KE Bennin, J Keung, A Monden, P Phannachitta, S Mensah
2017 ACM/IEEE International Symposium on Empirical Software Engineering and …, 2017
482017
Duplex output software effort estimation model with self-guided interpretation
S Mensah, J Keung, MF Bosu, KE Bennin
Information and Software Technology 94, 1-13, 2018
462018
Bug localization with semantic and structural features using convolutional neural network and cascade forest
Y Xiao, J Keung, Q Mi, KE Bennin
Proceedings of the 22nd International Conference on Evaluation and …, 2018
432018
On the value of a prioritization scheme for resolving self-admitted technical debt
S Mensah, J Keung, J Svajlenko, KE Bennin, Q Mi
Journal of Systems and Software 135, 37-54, 2018
422018
Effects of geographical, socio-cultural and temporal distances on communication in global software development during requirements change management a pilot study
AA Khan, J Keung, S Hussain, KE Bennin
2015 International Conference on Evaluation of Novel Approaches to Software …, 2015
362015
An empirical study on the effectiveness of data resampling approaches for cross‐project software defect prediction
KE Bennin, A Tahir, SG MacDonell, J Börstler
IET Software 16 (2), 185-199, 2022
312022
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