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| license: apache-2.0 |
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| # Dataset Card for Dataset Name |
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| ## Dataset Description |
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| - **Repository:** https://github.com/amazon-science/recode/tree/main |
| - **Paper:** https://arxiv.org/abs/2212.10264 |
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| ### Dataset Summary |
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| The Recode benchmark proposes to apply code and natural language transformations to code-generation benchmarks to evaluate the robustness of code-generation models. |
| This dataset contains the perturbed version of HumanEval that they released. |
| It was automatically generated from the [HumanEval](https://huggingface.co/datasets/openai_humaneval) dataset. |
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| ### Subsets |
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| There are four transformation categories that form the subsets of this dataset: `func_name`, `nlaugmenter`, `natgen` and `format`. |
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| ### Languages |
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| The programming problems are written in Python and contains docstrings and comments in English. |
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| ## Dataset Structure |
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| ### Data Instances |
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| [More Information Needed] |
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| ### Data Fields |
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| - `task_id`: ID of the original HumanEval example |
| - `prompt`: the perturbed prompt |
| - `entry_point`: entry point for test |
| - `canonical_solution`: solution for the problem in the `prompt` |
| - `test`: contains function to test generated code for correctness |
| - `seed`: seed of the perturbed prompt |
| - `perturbation_name`: name of the perturbation |
| - `partial`: partial solution to the problem. This field is only present for transformation categories that affect a partial solution: `natgen` and `format`. |
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| ### Data Splits |
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| The dataset only has a test split. |
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| ## Dataset Creation |
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| ### Curation Rationale |
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| [More Information Needed] |
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| ### Source Data |
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| #### Initial Data Collection and Normalization |
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| [More Information Needed] |
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| #### Who are the source language producers? |
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| [More Information Needed] |
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| ### Annotations |
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| #### Annotation process |
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| [More Information Needed] |
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| #### Who are the annotators? |
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| [More Information Needed] |
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| ### Personal and Sensitive Information |
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| [More Information Needed] |
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| ## Considerations for Using the Data |
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| ### Social Impact of Dataset |
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| [More Information Needed] |
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| ### Discussion of Biases |
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| [More Information Needed] |
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| ### Other Known Limitations |
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| [More Information Needed] |
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| ## Additional Information |
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| ### Dataset Curators |
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| [More Information Needed] |
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| ### Licensing Information |
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| [More Information Needed] |
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| ### Citation Information |
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| ``` |
| @article{wang2022recode, |
| title={ReCode: Robustness Evaluation of Code Generation Models}, |
| author={Wang, Shiqi and Li, Zheng and Qian, Haifeng and Yang, Chenghao and Wang, Zijian and Shang, Mingyue and Kumar, Varun and Tan, Samson and Ray, Baishakhi and Bhatia, Parminder and others}, |
| journal={arXiv preprint arXiv:2212.10264}, |
| year={2022} |
| } |
| ``` |
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| ### Contributions |
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| [More Information Needed] |
