| Value-cognitive boosting with a support vector machine for cross-project defect prediction D Ryu, O Choi, J Baik Empirical Software Engineering 21 (1), 43-71, 2016 | 218 | 2016 |
| A transfer cost-sensitive boosting approach for cross-project defect prediction D Ryu, JI Jang, J Baik Software Quality Journal 25 (1), 235-272, 2017 | 173 | 2017 |
| A hybrid instance selection using nearest-neighbor for cross-project defect prediction D Ryu, JI Jang, J Baik Journal of Computer Science and Technology 30 (5), 969-980, 2015 | 139 | 2015 |
| Effective multi-objective naïve Bayes learning for cross-project defect prediction D Ryu, J Baik Applied Soft Computing 49, 1062-1077, 2016 | 114 | 2016 |
| Location-based web service QoS prediction via preference propagation to address cold start problem D Ryu, K Lee, J Baik IEEE Transactions on Services Computing 14 (3), 736-746, 2021 | 78 | 2021 |
| Improving vulnerability prediction accuracy with secure coding standard violation measures J Yang, D Ryu, J Baik 2016 International Conference on Big Data and Smart Computing (BigComp), 115-122, 2016 | 43 | 2016 |
| Exploring LLM-based automated repairing of Ansible script in edge-cloud infrastructures S Kwon, S Lee, T Kim, D Ryu, J Baik Journal of web engineering 22 (6), 889-912, 2023 | 30 | 2023 |
| HASPO: Harmony Search-Based Parameter Optimization for Just-in-Time Software Defect Prediction in Maritime Software J Kang, S Kwon, D Ryu, J Baik applied sciences 11 (5), 1-25, 2021 | 22 | 2021 |
| Holistic parameter optimization for software defect prediction J Lee, J Choi, D Ryu, S Kim IEEE Access 10, 106781-106797, 2022 | 18 | 2022 |
| Predicting just‐in‐time software defects to reduce post‐release quality costs in the maritime industry J Kang, D Ryu, J Baik Software: Practice and Experience 51 (4), 748-771, 2021 | 17 | 2021 |
| Improving prediction robustness of VAB-SVM for cross-project defect prediction D Ryu, O Choi, J Baik 2014 IEEE 17th International Conference on Computational Science and …, 2014 | 13 | 2014 |
| Just-in-time defect prediction for self-driving software via a deep learning model J Choi, T Kim, D Ryu, J Baik, S Kim Journal of Web Engineering 22 (2), 303-326, 2023 | 10 | 2023 |
| HOTFUZ: Cost‐effective higher‐order mutation‐based fault localization JI Jang, D Ryu, J Baik Software Testing, Verification and Reliability 32 (8), e1802, 2022 | 10 | 2022 |
| An integrated software management tool for adopting software product lines K Park, D Ryu, J Baik 2012 IEEE/ACIS 11th International Conference on Computer and Information …, 2012 | 9 | 2012 |
| Exploring the feasibility of chatgpt for improving the quality of ansible scripts in edge-cloud infrastructures through code recommendation S Kwon, S Lee, T Kim, D Ryu, J Baik International Conference on Web Engineering, 75-83, 2023 | 8 | 2023 |
| GAIN-QoS: A novel QoS prediction model for edge computing J Choi, J Lee, D Ryu, S Kim, J Baik Journal of Web Engineering 21 (1), 27-52, 2022 | 8 | 2022 |
| eCPDP: Early cross-project defect prediction S Kwon, D Ryu, J Baik 2021 IEEE 21st International Conference on Software Quality, Reliability and …, 2021 | 8 | 2021 |
| Pre-trained model-based software defect prediction for edge-cloud systems S Kwon, S Lee, D Ryu, J Baik Journal of Web Engineering 22 (2), 255-278, 2023 | 7 | 2023 |
| Codebert based software defect prediction for edge-cloud systems S Kwon, JI Jang, S Lee, D Ryu, J Baik International Conference on Web Engineering, 11-21, 2022 | 7 | 2022 |
| Heterogeneous defect prediction through correlation-based selection of multiple source projects and ensemble learning E Kim, J Baik, D Ryu 2021 IEEE 21st International Conference on Software Quality, Reliability and …, 2021 | 6 | 2021 |
Jongmoon BaikProfessor at School of Computing, KAISTVerified email at kaist.ac.kr
