Publications

• Majidi, Forough, Mohammad Mehdi Morovati, Foutse Khomh, and Heng Li. “LLM Serving in the Wild: An Empirical Study of Frameworks, Methods, and System Designs.” arXiv preprint arXiv:2608.03036 (2026).Link
• Mazloomzadeh, Iren, Mohammad Mehdi Morovati, and Foutse Khomh. “How Do AI Coding Agents Contribute to Software Development? an Empirical Study of Agentic Pull Requests.” arXiv preprint arXiv:2607.21832 (2026).Link
• Shah, Mehil B., Mohammad Mehdi Morovati, Mohammad Masudur Rahman, and Foutse Khomh. “Characterizing faults in agentic AI: A taxonomy of types, symptoms, and root causes.” arXiv preprint arXiv:2603.06847 (2026).Link
• Taraghi, Mina, Mohammad Mehdi Morovati, and Foutse Khomh. “Real faults in Model Context Protocol (MCP) software: a comprehensive taxonomy.” arXiv preprint arXiv:2603.05637 (2026). Link
• Morovati, Mohammad Mehdi, Amin Nikanjam, and Foutse Khomh. “Fault Localization in Deep Learning-based Software: A System-level Approach” arXiv preprint arXiv:2411.08172 (2024). Link
• Morovati, Mohammad Mehdi, Florian Tambon, Mina Taraghi, Amin Nikanjam, and Foutse Khomh. “Common challenges of deep reinforcement learning applications development: an empirical study” Empirical Software Engineering 29, no. 4 (2024): 95. Link
• Morovati, Mohammad Mehdi, Amin Nikanjam, Florian Tambon, Foutse Khomh, and Zhen Ming Jiang. “Bug characterization in machine learning-based systems” Empirical Software Engineering 29, no. 1 (2024): 14. Link
• Morovati, Mohammad Mehdi, Amin Nikanjam, Foutse Khomh, and Zhen Ming Jiang. “Bugs in machine learning-based systems: a faultload benchmark” Empirical Software Engineering 28, no. 3 (2023): 62. Link
• Openja, Moses, Mohammad Mehdi Morovati, Le An, Foutse Khomh, and Mouna Abidi. “Technical debts and faults in open-source quantum software systems: An empirical study” Journal of Systems and Software 193 (2022): 111458. Link
• Nikanjam, Amin, Mohammad Mehdi Morovati, Foutse Khomh, and Houssem Ben Braiek. “Faults in deep reinforcement learning programs: a taxonomy and a detection approach” Automated software engineering 29, no. 1 (2022): 8. Link
• Nikanjam, Amin, Houssem Ben Braiek, Mohammad Mehdi Morovati, and Foutse Khomh. “Automatic fault detection for deep learning programs using graph transformations” ACM Transactions on Software Engineering and Methodology (TOSEM) 31, no. 1 (2021): 1-27. Link