Publications

Dmytro Humeniuk, Houssem Ben Braiek, Thomas Reid, Foutse Khomh (2024). In-Simulation Testing of Deep Learning Vision Models in Autonomous Robotic Manipulators. In ASE'24.

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Houssem Ben Braiek, Foutse Khomh (2024). Machine Learning Robustness: A Primer. Chapter in Book: Trustworthy AI in Medical imaging, Elservier.

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Ahmed Haj Yahmed, Rached Bouchoucha, Houssem Ben Braiek, Foutse Khomh (2023). An Intentional Forgetting-Driven Self-Healing Method For Deep Reinforcement Learning Systems. In ASE'23.

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Rached Bouchoucha, Houssem Ben Braiek, Foutse Khomh, Sonia Bouzidi, Rania Zaatour (2023). Robustness assessment of hyperspectral image CNNs using metamorphic testing. In IST.

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Houssem Ben Braiek, Ali Tfaily, Foutse Khomh, Thomas Reid, Ciro Guida (2022). SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design. In ASE'22.

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Houssem Ben Braiek, Thomas Reid, Foutse Khomh (2022). Physics-Guided Adversarial Machine Learning for Aircraft Systems Simulation. In Transactions on Reliability.

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Ahmed Haj Yahmed, Houssem Ben Braiek, Foutse Khomh, Sonia Bouzidi, Rania Zaatour (2022). DiverGet: A Search-Based Software Testing Approach for Deep Neural Network Quantization Assessment. In EMSE.

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Houssem Ben Braiek, Foutse Khomh (2022). Testing Feedforward Neural Networks Training Programs. In TOSEM.

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Amin Nikanjam, Mohammad Mehdi Morovati, Foutse Khomh, Houssem Ben Braiek (2021). Faults in Deep Reinforcement Learning Programs: a Taxonomy and a Detection Approach. In Autom Softw Eng.

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Amin Nikanjam, Houssem Ben Braiek, Mohammad Mehdi Morovati, Foutse Khomh (2021). Automatic Fault Detection for Deep Learning Programs Using Graph Transformations. In TOSEM.

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Ettore Merlo, Mira Marhaba, Foutse Khomh, Houssem Ben Braiek, Giuliano Antoniol (2020). Models of Computational Profiles to Study the Likelihood of DNN Metamorphic Test Cases. In iMLSE'20.

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Hadhemi Jebnoun, Houssem Ben Braiek, Mohammad Masudur Rahman, Foutse Khomh (2020). The Scent of Deep Learning Code: An Empirical Study. In MSR'20.

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Houssem Ben Braiek, Foutse Khomh (2020). On Testing Machine Learning Programs. In JSS.

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Houssem Ben Braiek, Foutse Khomh (2019). DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks. In ICSME'19.

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Houssem Ben Braiek, Foutse Khomh (2019). TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs. In QRS'19.

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Houssem Ben Braiek, Foutse Khomh, Bram Adams (2018). The Open-Closed Principle of Modern Machine Learning Frameworks'. In MSR'18.

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Sonia Bouzidi, Houssem Ben Braiek (2018). Improved Algorithm for Hyperspectral Image Classification. In J. of Electronic Imaging.

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