| Effective white-box testing of deep neural networks with adaptive neuron-selection strategy S Lee, S Cha, D Lee, H Oh Proceedings of the 29th ACM SIGSOFT International Symposium on Software …, 2020 | 56 | 2020 |
| Automatically generating search heuristics for concolic testing S Cha, S Hong, J Lee, H Oh Proceedings of the 40th International Conference on Software Engineering …, 2018 | 33 | 2018 |
| Concolic testing with adaptively changing search heuristics S Cha, H Oh Proceedings of the 2019 27th ACM Joint Meeting on European Software …, 2019 | 19 | 2019 |
| Learning a strategy for choosing widening thresholds from a large codebase S Cha, S Jeong, H Oh Asian Symposium on Programming Languages and Systems, 25-41, 2016 | 17 | 2016 |
| Template-guided concolic testing via online learning S Cha, S Lee, H Oh Proceedings of the 33rd ACM/IEEE International Conference on Automated …, 2018 | 14 | 2018 |
| Enhancing dynamic symbolic execution by automatically learning search heuristics S Cha, S Hong, J Bak, J Kim, J Lee, H Oh IEEE Transactions on Software Engineering 48 (9), 3640-3663, 2021 | 10 | 2021 |
| Making symbolic execution promising by learning aggressive state-pruning strategy S Cha, H Oh Proceedings of the 28th ACM Joint Meeting on European Software Engineering …, 2020 | 8 | 2020 |
| A scalable learning algorithm for data-driven program analysis S Cha, S Jeong, H Oh Information and Software Technology 104, 1-13, 2018 | 7 | 2018 |
| Learning Seed-Adaptive Mutation Strategies for Greybox Fuzzing M Lee, S Cha, H Oh 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE …, 2023 | 4 | 2023 |
| SymTuner: maximizing the power of symbolic execution by adaptively tuning external parameters S Cha, M Lee, S Lee, H Oh Proceedings of the 44th International Conference on Software Engineering …, 2022 | | 2022 |
| METHOD FOR AUTOMATICALLY PRUNING SEARCH SPACE OF SYMBOLIC EXECUTION VIA MACHINE LEARNING H OH, S Cha US Patent App. 17/496,012, 2022 | | 2022 |
