KABORE, A. K. (2024). Neural Vulnerable Program Repair [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/60869 |
KABORE, A. K., Barr, E. T., KLEIN, J., & Bissyandé, T. F. (2023). CodeGrid: A Grid Representation of Code. In R. Just (Ed.), ISSTA 2023 - Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis. Association for Computing Machinery, Inc. doi:10.1145/3597926.3598141 Peer reviewed |
Samhi, J., Kober, K., Kabore, A. K., Arzt, S., Bissyande, T. F. D. A., & Klein, J. (2023). Negative Results of Fusing Code and Documentation for Learning to Accurately Identify Sensitive Source and Sink Methods An Application to the Android Framework for Data Leak Detection. In 30th IEEE International Conference on Software Analysis, Evolution and Reengineering. Peer reviewed |
Tian, H., Li, Y., Pian, W., Kabore, A. K., Liu, K., Habib, A., Klein, J., & Bissyande, T. F. D. A. (2022). Predicting Patch Correctness Based on the Similarity of Failing Test Cases. ACM Transactions on Software Engineering and Methodology. doi:10.1145/3511096 Peer Reviewed verified by ORBi |
Tian, H., Liu, K., Li, Y., Kabore, A. K., Koyuncu, A., Habib, A., Li, L., Wen, J., Klein, J., & Bissyande, T. F. D. A. (2022). The Best of Both Worlds: Combining Learned Embeddings with Engineered Features for Accurate Prediction of Correct Patches. ACM Transactions on Software Engineering and Methodology. Peer reviewed |
Keller, P., Kabore, A. K., Plein, L., Klein, J., Le Traon, Y., & Bissyande, T. F. D. A. (2021). What You See is What it Means! Semantic Representation Learning of Code based on Visualization. ACM Transactions on Software Engineering and Methodology. doi:10.1145/3485135 Peer Reviewed verified by ORBi |
Daoudi, N., Samhi, J., Kabore, A. K., Allix, K., Bissyande, T. F. D. A., & Klein, J. (2021). DexRay: A Simple, yet Effective Deep Learning Approach to Android Malware Detection Based on Image Representation of Bytecode. In Communications in Computer and Information Science. Springer. doi:10.1007/978-3-030-87839-9_4 Peer reviewed |
Tian, H., Liu, K., Kabore, A. K., Koyuncu, A., Li, L., Klein, J., & Bissyande, T. F. D. A. (2020). Evaluating Representation Learning of Code Changes for Predicting Patch Correctness in Program Repair. In H. Tian, 35th IEEE/ACM International Conference on Automated Software Engineering, September 21-25, 2020, Melbourne, Australia. doi:10.1145/3324884.3416532 Peer reviewed |