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Benjamin Steenhoek
Benjamin Steenhoek
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An empirical study of deep learning models for vulnerability detection
B Steenhoek, MM Rahman, R Jiles, W Le
2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE …, 2023
352023
Validating static warnings via testing code fragments
A Kallingal Joshy, X Chen, B Steenhoek, W Le
Proceedings of the 30th ACM SIGSOFT International Symposium on Software …, 2021
112021
Traced: Execution-aware pre-training for source code
Y Ding, B Steenhoek, K Pei, G Kaiser, W Le, B Ray
Proceedings of the 46th IEEE/ACM International Conference on Software …, 2024
102024
Dataflow Analysis-Inspired Deep Learning for Efficient Vulnerability Detection
B Steenhoek, H Gao, W Le
Proceedings of the 46th IEEE/ACM International Conference on Software …, 2024
52024
Reinforcement Learning from Automatic Feedback for High-Quality Unit Test Generation
B Steenhoek, M Tufano, N Sundaresan, A Svyatkovskiy
arXiv preprint arXiv:2310.02368, 2023
32023
Deepdfa: Dataflow analysis-guided efficient graph learning for vulnerability detection
B Steenhoek, W Le, H Gao
22022
A Comprehensive Study of the Capabilities of Large Language Models for Vulnerability Detection
B Steenhoek, MM Rahman, MK Roy, MS Alam, ET Barr, W Le
arXiv preprint arXiv:2403.17218, 2024
2024
Do Language Models Learn Semantics of Code? A Case Study in Vulnerability Detection
B Steenhoek, MM Rahman, S Sharmin, W Le
arXiv preprint arXiv:2311.04109, 2023
2023
Reproducing Failures in Fault Signatures
AK Joshy, B Steenhoek, X Guo, W Le
arXiv preprint arXiv:2309.11004, 2023
2023
Reproducing Failures in Fault Signatures
A Kallingal Joshy, B Steenhoek, X Guo, W Le
arXiv e-prints, arXiv: 2309.11004, 2023
2023
A Study of Static Warning Cascading Tools (Experience Paper)
X Guo, AK Joshy, B Steenhoek, W Le, L Flynn
arXiv preprint arXiv:2305.02515, 2023
2023
Refactoring programs to improve the performance of deep learning for vulnerability detection
BJ Steenhoek
Iowa State University, 2021
2021
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