Houssem Ben Braiek

According to our database, Houssem Ben Braiek authored at least 17 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Trimming the Risk: Towards Reliable Continuous Training for Deep Learning Inspection Systems.

Altaf Allah Abbassi, Houssem Ben Braiek, Foutse Khomh, Thomas Reid

CoRR, 2024

Machine Learning Robustness: A Primer.

Houssem Ben Braiek, Foutse Khomh

CoRR, 2024

2023

Physics-Guided Adversarial Machine Learning for Aircraft Systems Simulation.

Houssem Ben Braiek, Thomas Reid, Foutse Khomh

IEEE Trans. Reliab., September, 2023

Testing Feedforward Neural Networks Training Programs.

Houssem Ben Braiek, Foutse Khomh

ACM Trans. Softw. Eng. Methodol., July, 2023

Robustness assessment of hyperspectral image CNNs using metamorphic testing.

Rached Bouchoucha, Houssem Ben Braiek, Foutse Khomh, Sonia Bouzidi, Rania Zaatour

Inf. Softw. Technol., 2023

An Intentional Forgetting-Driven Self-Healing Method for Deep Reinforcement Learning Systems.

Ahmed Haj Yahmed, Rached Bouchoucha, Houssem Ben Braiek, Foutse Khomh

Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering, 2023

2022

Automatic Fault Detection for Deep Learning Programs Using Graph Transformations.

Amin Nikanjam, Houssem Ben Braiek, Mohammad Mehdi Morovati, Foutse Khomh

ACM Trans. Softw. Eng. Methodol., 2022

DiverGet: a Search-Based Software Testing approach for Deep Neural Network Quantization assessment.

Ahmed Haj Yahmed, Houssem Ben Braiek, Foutse Khomh, Sonia Bouzidi, Rania Zaatour

Empir. Softw. Eng., 2022

Faults in deep reinforcement learning programs: a taxonomy and a detection approach.

Amin Nikanjam, Mohammad Mehdi Morovati, Foutse Khomh, Houssem Ben Braiek

Autom. Softw. Eng., 2022

SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design.

Houssem Ben Braiek, Ali Tfaily, Foutse Khomh, Thomas Reid, Ciro Guida

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, 2022

2021

Models of Computational Profiles to Study the Likelihood of DNN Metamorphic Test Cases.

Ettore Merlo, Mira Marhaba, Foutse Khomh, Houssem Ben Braiek, Giuliano Antoniol

CoRR, 2021

2020

On testing machine learning programs.

Houssem Ben Braiek, Foutse Khomh

J. Syst. Softw., 2020

The Scent of Deep Learning Code: An Empirical Study.

Hadhemi Jebnoun, Houssem Ben Braiek, Mohammad Masudur Rahman, Foutse Khomh

Proceedings of the MSR '20: 17th International Conference on Mining Software Repositories, 2020

2019

TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs.

Houssem Ben Braiek, Foutse Khomh

Proceedings of the 19th IEEE International Conference on Software Quality, 2019

DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks.

Houssem Ben Braiek, Foutse Khomh

Proceedings of the 2019 IEEE International Conference on Software Maintenance and Evolution, 2019

2018

Improved algorithm for hyperspectral image classification.

Sonia Bouzidi, Houssem Ben Braiek

J. Electronic Imaging, 2018

The open-closed principle of modern machine learning frameworks.

Houssem Ben Braiek, Foutse Khomh, Bram Adams

Proceedings of the 15th International Conference on Mining Software Repositories, 2018