PI: Sandareka Wickramanayake
We propose to advance automated program repair by leveraging natural language processing techniques, iterative repair strategies, and explainable AI frameworks to enhance accuracy, robustness, and interpretability of repair systems.
Workshop Papers
Jayanath Senevirathna, Ayesh Vininda, Prasad Sandaruwan, Ridwan Shariffdeen, Sandareka Wickramanayake, and Nisansa de Silva, "FusionRepair: Iterative Multi-Line APR via Fusion", in IEEE/ACM International Workshop on Automated Program Repair (APR), 2025, pp. 27--34. doi: 10.1109/APR66717.2025.00009
Nethum Lamahewage, Nimantha Cooray, Ridwan Shariffdeen, Sandareka Wickramanayake, and Nisansa de Silva, "SCHOLIA-An XAI Framework for APR", in IEEE/ACM International Workshop on Automated Program Repair (APR), 2025, pp. 19--26. doi: 10.1109/APR66717.2025.00008
Extended Abstracts
H L S Sankaja, R P G Sandeeptha, R M R U Ranasingha, S Wickramanayake, and Nisansa de Silva, "Generating Natural Language Explanations for Automated Program Repair Generated Patches", in International Conference of Sabaragamuwa University of Sri Lanka, 2025, pp. 61.
Preprints
Kaushal Kahapola, Sharada Galappaththi, Dinith Ranasinghe, Ridwan Shariffdeen, Nisansa de Silva, Srinath Perera, and Sandareka Wickramanayake, "JavaBackports: A Dataset for Benchmarking Automated Backporting in Java", in 23rd International Conference on Mining Software Repositories (MSR), 2026.
