| | --- |
| | 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-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 implementation |
| | - `fixed_code`: The correct implementation |
| | - `unit_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 |
| |
|
| | ```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.}, |
| | } |
| | ``` |
