SiblingRepair: Sibling-Based Multi-Hunk Repair with Large Language Models
Xinyu Liu, Jiayu Ren, Yusen Wang, Qi Xin, Xiaoyuan Xie, and Jifeng Xuan

TL;DR
SiblingRepair is a novel LLM-based multi-hunk automated program repair technique that effectively identifies and repairs related code siblings without relying on commit history or strict AST matching.
Contribution
It introduces a sibling detection and repair approach using semantic code matching and LLMs, outperforming state-of-the-art methods like Hercules.
Findings
SiblingRepair outperforms Hercules and other SOTA multi-hunk repair techniques.
It demonstrates high repair efficiency and effective sibling detection.
Limited impact of LLM data leakage on repair results.
Abstract
Developers often make similar mistakes across code locations implementing related functionalities. These locations, called siblings, share similar issues and require similar fixes. Accurately identifying siblings and consistently repairing them are crucial for automated program repair. Hercules is a SOTA technique designed for sibling repair. However, it is limited by strong assumptions about sibling locations and commit-history availability, rigid AST-based sibling matching, and inflexible template-based patch generation. To address these limitations, we present SiblingRepair, a new LLM-based multi-hunk APR technique specialized for sibling repair. Starting from a suspicious location identified by spectrum-based fault localization, SiblingRepair searches for semantically related sibling candidates using token- and embedding-based code matching, without restricting discovery to…
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