Yiran Wang, Jakob Hoffmann, Jürgen Cito, and Dániel Varró. 2026. Beyond Crash Resolution: Evaluating LLM Agents for Repairing Machine Learning Notebooks. Submitted.
Yiran Wang, José Antonio Hernández López, Ulf Nilsson, and Dániel Varró. 2026. CRANE-LLM: Runtime-Augmented LLMs for Crash Prediction and Diagnosis in ML Notebooks. Accepted to SCAM2026. arXiv: 2602.18537
Yiran Wang, José Antonio Hernández López, Ulf Nilsson, and Dániel Varró. 2026. JunoBench: A Benchmark Dataset of Crashes in Python Machine Learning Jupyter Notebooks. In Proceedings of the 3rd ACM International Conference on AI-Powered Software (AIware '26), Montreal, QC, Canada, pp. 406–413. doi: 10.1145/3805760.3814934
Yiran Wang, Willem Meijer, José Antonio Hernández López, Ulf Nilsson, and Dániel Varró. 2025. Why Do Machine Learning Notebooks Crash? An Empirical Study on Public Python Jupyter Notebooks. IEEE Transactions on Software Engineering, vol. 51, no. 7, pp. 2181–2196. doi: 10.1109/TSE.2025.3574500
Yiran Wang, José Antonio Hernández López, Ulf Nilsson, and Dániel Varró. 2024. Using Run-Time Information to Enhance Static Analysis of Machine Learning Code in Notebooks. In Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering (FSE 2024), Porto de Galinhas, Brazil, pp. 497–501. CORE rank: A*. doi: 10.1145/3663529.3663785
Yiran Wang. 2023. Early Detection of Defects in Machine Learning Programs by Semi-Static Analysis. Accepted for presentation at Doctoral Forum at the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE'23), Luxembourg, 11-15 September, 2023. doi: 10.5281/zenodo.20793551