metadata
license: mit
Dataset Description
- Repository: MORepair
- Paper: MORepair: Teaching LLMs to Repair Code via Multi-Objective Fine-tuning
- Point of Contact: Boyang Yang
Dataset Summary
EvalRepair-Java is a benchmark for evaluating Java program repair performance, derived from HumanEval. It contains 163 single-function repair tasks, each with a buggy implementation and its corresponding fixed version.
Supported Tasks
- Program Repair: Fixing bugs in Java functions
- Code Generation: Generating correct implementations from buggy code
Dataset Structure
Each row contains:
task_id
: Unique identifier for the task (same as HumanEval)buggy_code
: The buggy implementationfixed_code
: The correct implementationunit_test
: Unit tests for verifying the correctness of the implementation
Source Data
This dataset is derived from HumanEval, a benchmark for evaluating code generation capabilities. We manually introduced bugs into the original implementations and verified the fixes.
Citation
@article{morepair,
author = {Yang, Boyang and Tian, Haoye and Ren, Jiadong and Zhang, Hongyu and Klein, Jacques and Bissyande, Tegawende and Le Goues, Claire and Jin, Shunfu},
title = {MORepair: Teaching LLMs to Repair Code via Multi-Objective Fine-Tuning},
year = {2025},
publisher = {Association for Computing Machinery},
issn = {1049-331X},
url = {https://doi.org/10.1145/3735129},
doi = {10.1145/3735129},
journal = {ACM Trans. Softw. Eng. Methodol.},
}