| Classifying false positive static checker alarms in continuous integration using convolutional neural networks S Lee, S Hong, J Yi, T Kim, CJ Kim, S Yoo 2019 12th IEEE Conference on Software Testing, Validation and Verification …, 2019 | 8 | 2019 |
| Amortised Deep Parameter Optimisation of GPGPU Work Group Size for OpenCV J Sohn, S Lee, S Yoo International Symposium on Search Based Software Engineering, 211-217, 2016 | 7 | 2016 |
| MOAD: Modeling observation-based approximate dependency S Lee, D Binkley, R Feldt, N Gold, S Yoo 2019 19th International Working Conference on Source Code Analysis and …, 2019 | 5 | 2019 |
| PyGGI: Python General framework for Genetic Improvement G An, J Kim, S Lee, S Yoo 한국정보과학회 학술발표논문집, 536-538, 2017 | 5 | 2017 |
| Evaluating lexical approximation of program dependence S Lee, D Binkley, N Gold, S Islam, J Krinke, S Yoo Journal of Systems and Software 160, 110459, 2020 | 3 | 2020 |
| Genetic Improvement@ ICSE 2020 WB Langdon, W Weimer, J Petke, E Fredericks, S Lee, E Winter, M Basios, ... ACM SIGSOFT Software Engineering Notes 45 (4), 24-30, 2020 | 1 | 2020 |
| Scalable and approximate program dependence analysis S Lee Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 1 | 2020 |
| Observation-based approximate dependency modeling and its use for program slicing S Lee, D Binkley, R Feldt, N Gold, S Yoo Journal of Systems and Software 179, 110988, 2021 | | 2021 |
| Causal Program Dependence Analysis S Lee, D Binkley, R Feldt, N Gold, S Yoo arXiv preprint arXiv:2104.09107, 2021 | | 2021 |
| MOBS: multi-operator observation-based slicing using lexical approximation of program dependence S Lee, D Binkley, N Gold, S Islam, J Krinke, S Yoo Proceedings of the 40th International Conference on Software Engineering …, 2018 | | 2018 |
| Hyperheuristic Observation Based Slicing of Guava S Lee, S Yoo International Symposium on Search Based Software Engineering, 175-180, 2017 | | 2017 |
Shin YooKorea Advanced Institute of Science and Technologykaist.ac.kr의 이메일 확인됨
