Publications

Sophie Fortz, Fatemeh Ghassemi, Léo Henry, Falk Howar, Thomas Neele, Jurriaan Rot, Marnix Suilen (2026). A Research Agenda for Active Automata Learning. In STTT.
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Avner Bensoussan, Elena Chachkarova, Karine Even-Mendoza, Sophie Fortz, Vasileios Klimis, Mohammadreza Mousavi (2026). Toward Live Noise Fingerprinting for Discrepancy Analysis in Quantum Software Engineering. In the Short Papers, Vision and Emerging Results track of ICST 2026.
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Avner Bensoussan, Elena Chachkarova, Karine Even-Mendoza, Sophie Fortz, Connor Lenihan (2025). AccelerQ: Accelerating Quantum Eigensolvers With Machine Learning on Quantum Simulators. In OOPSLA 2025.
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Vasileios Klimis, Avner Bensoussan, Elena Chachkarova, Karine Even-Mendoza, Sophie Fortz, Connor Lenihan (2025). Shaking Up Quantum Simulators with Fuzzing and Rigour. In OOPSLA 2025.
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Giordano D'Aloisio, Sophie Fortz, Carol Hanna, Daniel Fortunato, Avner Bensoussan, Eñaut Mendiluze Usandizaga, Federica Sarro (2024). Exploring LLM-Driven Explanations for Quantum Algorithms. In the Vision and Emerging Results track of ESEM 2024.
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Sophie Fortz, Paul Temple, Xavier Devroey, Patrick Heymans, Gilles Perrouin (2024). VaryMinions: Leveraging RNNs to Identify Variants in Variability-intensive Systems’ Logs. In EMSE.
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Sophie Fortz, Paul Temple, Xavier Devroey, Gilles Perrouin (2024). Towards Feature-based ML-enabled Behaviour Location. In VaMoS 2024.
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Sophie Fortz (2023). Doctoral Symposium: Variability-Aware Behavioural Learning. In the Doctoral Symposium of SPLC 2023.
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Edilton Lima Dos Santos, Sophie Fortz, Pierre-Yves Schobbens, Gilles Perrouin (2022). Behavioral Maps: Identifying Architectural Smells in Self-adaptive Systems at Runtime.
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Edilton Lima Dos Santos, Sophie Fortz, Pierre-Yves Schobbens, Gilles Perrouin (2022). Identifying Architectural Smells in Self-Adaptive Systems at Runtime.
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