ATTAOUI, M. O., FAHMY, H., PASTORE, F., & BRIAND, L. (In press). Supporting Safety Analysis of Image-processing DNNs through Clustering-based Approaches. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/58139. doi:10.1145/3643671 |
Fahmy, H., Pastore, F., Briand, L., & Stifter, T. (2023). Simulator-based explanation and debugging of hazard-triggering events in DNN-based safety-critical systems. ACM Transactions on Software Engineering and Methodology. doi:10.1145/3569935 Peer reviewed |
Fahmy, H. (2023). Supporting Safety Analysis of Deep Neural Networks with Automated Debugging and Repair [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/55149 |
Attaoui, M. O., Fahmy, H., Pastore, F., & Briand, L. (2022). Black-box Safety Analysis and Retraining of DNNs based on Feature Extraction and Clustering. ACM Transactions on Software Engineering and Methodology. doi:10.1145/3550271 Peer Reviewed verified by ORBi |
Fahmy, H., Pastore, F., & Briand, L. (2022). HUDD: A tool to debug DNNs for safety analysis. In 2022 IEEE/ACM 44th International Conference on Software Engineering. Pittsburgh, PA, United States: ACM/IEEE. doi:10.1145/3510454.3516858 Peer reviewed |
Fahmy, H., Pastore, F., Bagherzadeh, M., & Briand, L. (May 2021). Supporting DNN Safety Analysis and Retraining through Heatmap-based Unsupervised Learning. IEEE Transactions on Reliability, 70 (4), 1641-1657. doi:10.1109/TR.2021.3074750 Peer reviewed |