Quality issues in Machine Learning Software Systems. - Pierre-Olivier Côté; Amin Nikanjam; Rached Bouchoucha; Foutse Khomh (CoRR, 2022)

Can Ensembling Pre-processing Algorithms Lead to Better Machine Learning Fairness? - Khaled Badran; Pierre-Olivier Côté; Amanda Kolopanis; Rached Bouchoucha; Antonio Collante; Diego Elias Costa; Emad Shihab; Foutse Khomh (CoRR, 2022)

An Intentional Forgetting-Driven Self-Healing Method for Deep Reinforcement Learning Systems. - Ahmed Haj Yahmed; Rached Bouchoucha; Houssem Ben Braiek; Foutse Khomh (ASE, 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)

Can Ensembling Preprocessing Algorithms Lead to Better Machine Learning Fairness? - Khaled Badran; Pierre-Olivier Côté; Amanda Kolopanis; Rached Bouchoucha; Antonio Collante; Diego Elias Costa; Emad Shihab; Foutse Khomh (Computer, 2023)

Toward Debugging Deep Reinforcement Learning Programs with RLExplorer. - Rached Bouchoucha; Ahmed Haj Yahmed; Darshan Patil; Janarthanan Rajendran; Amin Nikanjam; Sarath Chandar; Foutse Khomh (ICSME, 2024)

Quality issues in machine learning software systems. - Pierre-Olivier Côté; Amin Nikanjam; Rached Bouchoucha; Ilan Basta; Mouna Abidi; Foutse Khomh (Empir. Softw. Eng., 2024)