MCRepair: Multi-Chunk Program Repair via Patch Optimization with Buggy Block
Jisung Kim, Byungjeong Lee · 2023
Automated program repair (APR) is a technology that identifies and repairs bugs automatically. However, repairing multi-chunk bugs remains a long-standing and challenging problem because an APR technique must consider dependencies and then reduce the large patch space. In addition, little is known about how to combine individual candidate patches even though multi-chunk bugs require combinations. Therefore, we propose a novel APR technique called multi-code repair (MCRepair), which applies a buggy block, patch optimization, and CodeBERT to target multi-chunk bugs. A buggy block is a novel method that binds buggy chunks into a multi-buggy chunk and preprocesses the chunk with its buggy contexts for patch space reduction and dependency problems. Patch optimization is a novel strategy that effectively combines the generated candidate patches with patch space reduction. In addition, CodeBERT, a BERT for source code datasets, is fine-tuned to address the lack of datasets and out-of-vocabulary problems. We conducted several experiments to evaluate our approach on six project modules of Defects4J. In the experiments using Defects4J, MCRepair repaired 66 bugs, including 22 multi-chunk bugs. Moreover, it fixed 19 unique bugs, including nine multi-chunk bugs, and improved 45--266% performance than the baselines.