---
license: mit
---

## Dataset Description

- **Repository:** [MORepair](https://github.com/buaabarty/morepair)
- **Paper:** [MORepair: Teaching LLMs to Repair Code via Multi-Objective Fine-tuning](https://arxiv.org/abs/2404.12636)
- **Point of Contact:** [Boyang Yang](mailto:yby@ieee.org)

### Dataset Summary

EvalRepair-C++ is a benchmark for evaluating C++ program repair performance, derived from HumanEval. It contains 164 single-function repair tasks, each with a buggy implementation and its corresponding fixed version.

### Supported Tasks

- Program Repair: Fixing bugs in C++ 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 implementation
- `fixed_code`: The correct implementation
- `unit_test`: Unit tests for verifying the correctness of the implementation
- `prompt`: Prefix information for generating fixed code

### 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

```bibtex
@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.},
}
```