Profil

KABORE Abdoul Kader

University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX

ORCID
0000-0002-3151-9433
Main Referenced Co-authors
KLEIN, Jacques  (7)
BISSYANDE, Tegawendé  (6)
TIAN, Haoye  (3)
HABIB, Andrew  (2)
KOYUNCU, Anil  (2)
Main Referenced Keywords
Abstract Syntax Trees (1); Android Security (1); Applications of AI (1); Artificial Intelligence (1); Code Classification (1);
Main Referenced Unit & Research Centers
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > TruX - Trustworthy Software Engineering (1)
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Trustworthy Software Engineering (TruX) (1)
Main Referenced Disciplines
Computer science (7)

Publications (total 7)

The most downloaded
113 downloads
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 https://hdl.handle.net/10993/48899

The most cited

57 citations (Scopus®)

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 https://hdl.handle.net/10993/45494

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

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