| On testing machine learning programs HB Braiek, F Khomh Journal of Systems and Software 164, 110542, 2020 | 162 | 2020 |
| The open-closed principle of modern machine learning frameworks HB Braiek, F Khomh, B Adams 2018 IEEE/ACM 15th International Conference on Mining Software Repositories …, 2018 | 39 | 2018 |
| Deepevolution: A search-based testing approach for deep neural networks HB Braiek, F Khomh 2019 IEEE International Conference on Software Maintenance and Evolution …, 2019 | 33 | 2019 |
| The scent of deep learning code: An empirical study H Jebnoun, H Ben Braiek, MM Rahman, F Khomh Proceedings of the 17th International Conference on Mining Software …, 2020 | 31 | 2020 |
| Faults in deep reinforcement learning programs: a taxonomy and a detection approach A Nikanjam, MM Morovati, F Khomh, H Ben Braiek Automated Software Engineering 29 (1), 1-32, 2022 | 23 | 2022 |
| Automatic fault detection for deep learning programs using graph transformations A Nikanjam, HB Braiek, MM Morovati, F Khomh ACM Transactions on Software Engineering and Methodology (TOSEM) 31 (1), 1-27, 2021 | 17 | 2021 |
| TFCheck: A tensorflow library for detecting training issues in neural network programs HB Braiek, F Khomh 2019 IEEE 19th international conference on software quality, reliability and …, 2019 | 10 | 2019 |
| Testing Feedforward Neural Networks Training Programs HB Braiek, F Khomh ACM Transactions on Software Engineering and Methodology, 2022 | 6 | 2022 |
| DiverGet: a Search-Based Software Testing approach for Deep Neural Network Quantization assessment AH Yahmed, HB Braiek, F Khomh, S Bouzidi, R Zaatour Empirical Software Engineering 27 (7), 193, 2022 | 5 | 2022 |
| Physics-Guided Adversarial Machine Learning for Aircraft Systems Simulation HB Braiek, T Reid, F Khomh IEEE Transactions on Reliability, 2022 | 2 | 2022 |
| Improved algorithm for hyperspectral image classification S Bouzidi, HB Braiek Journal of Electronic Imaging 27 (6), 063032, 2018 | 2 | 2018 |
| SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design H Ben Braiek, A Tfaily, F Khomh, T Reid, C Guida 37th IEEE/ACM International Conference on Automated Software Engineering, 1-13, 2022 | 1 | 2022 |
| Models of Computational Profiles to Study the Likelihood of DNN Metamorphic Test Cases E Merlo, M Marhaba, F Khomh, HB Braiek, G Antoniol arXiv preprint arXiv:2107.13491, 2021 | 1 | 2021 |
| Robustness Assessment of Hyperspectral Image Cnns Using Metamorphic Testing R Bouchoucha, H Ben Braiek, F Khomh, S Bouzidi, R Zaatour Foutse and Bouzidi, Sonia and Zaatour, Rania, Robustness Assessment of …, 0 | 1* | |
| Towards Debugging and Testing Deep Learning Systems HB Braiek Ecole Polytechnique, Montreal (Canada), 2019 | | 2019 |
| The Scent of Deep Learning Code H Jebnoun, HB Braiek, MM Rahman, F Khomh | | |
