| --- |
| license: |
| - apache-2.0 |
| size_categories: |
| - 100<n<1K |
| pretty_name: EditBench |
| tags: |
| - code |
| - code-editing |
| - code-generation |
| metrics: |
| - execution-accuracy |
| --- |
| |
| # EditBench Dataset |
|
|
| This dataset contains code editing tasks extracted from the EditBench evaluation framework specifically designed for evaluating model performance on code editing tasks. It is provided as a test-only benchmark. Each sample includes: |
|
|
| ## Core Files (Python) |
| - `original_code.py`: Starting code file |
| - `highlighted_code.py`: Specific section of code to be modified |
| - `instruction.txt`: User instructions for the task |
| - `test_code.py`: Tests that validate the implementation |
|
|
| ## Supporting Files (Python) |
| - `requirements.txt`: Dependencies needed to run the code |
| - `conftest.py`: Pytest configuration |
| - `test_utils.py`: Utilities for testing |
|
|
| ## Core Files (JavaScript) |
| - `original_code.js`: Starting code file (or .jsx) |
| - `highlighted_code.js`: Specific section of code to be modified |
| - `instruction.txt`: User instructions for the task |
| - `test_code`: Tests that validate the implementation (from tests/*.test.js) |
| - `package_json`: NPM package configuration |
| - `jest_setup`: Jest testing setup (if applicable) |
| - `babel_config`: Babel configuration (if applicable) |
| - `other_files`: Additional files needed for the project |
| |
| ## Dataset Statistics |
| - Total samples: 113 |
| - Python samples: 104 |
| - JavaScript samples: 9 |
| - Expected samples: 113 (57 easy + 56 hard questions) |
| - Found samples: 113 / 113 |
| |
| ## Usage |
| This dataset is provided as a test-only benchmark and can be loaded directly with the Hugging Face Datasets library: |
| |
| ```python |
| from datasets import load_dataset |
| |
| # Note that this dataset only has a 'test' split |
| dataset = load_dataset("your-username/editbench", split="test") |
| ``` |
| |
| ## Ethical Considerations and Limitations |
| |
| - This dataset is provided exclusively for benchmark/evaluation purposes |
| - Models should NOT be trained on this dataset, as it is specifically designed to test model capabilities |
| - Hugging Face's Terms of Service prohibit using benchmark datasets for training |
| - We recommend implementing your model's training pipeline to explicitly exclude this dataset |
| |
| ## Citation |
| If you use this dataset, please cite the original EditBench work. |
| |
| ``` |
| @misc{chi2025editbench, |
| title = {EditBench: Evaluating LLM Abilities to Perform Real-World Code Edits}, |
| author = {Wayne Chi and Valerie Chen and Ryan Shar and Aditya Mittal and Jenny Liang and Wei-Lin Chiang and Anastasios Nikolas Angelopoulos and Ion Stoica and Graham Neubig and Ameet Talwalkar and Chris Donahue}, |
| year = {2025}, |
| note = {arXiv preprint} |
| } |
| ``` |
| |
| ## Usage Restrictions |
| This dataset is provided for research and evaluation purposes only. By using this dataset, you agree not to: |
| 1. Train models on it (it is a benchmark dataset) |
| 2. Scrape or incorporate it into pretraining data |
| 3. Use it for any purpose other than evaluation |
| |
