|
--- |
|
license: apache-2.0 |
|
--- |
|
|
|
# Dataset Card for Dataset Name |
|
|
|
## Dataset Description |
|
|
|
- **Repository:** https://github.com/amazon-science/recode/tree/main |
|
- **Paper:** https://arxiv.org/abs/2212.10264 |
|
|
|
### Dataset Summary |
|
|
|
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. |
|
|
|
### Subsets |
|
|
|
There are four transformation categories that form the subsets of this dataset: `func_name`, `nlaugmenter`, `natgen` and `format`. |
|
|
|
### Languages |
|
|
|
The programming problems are written in Python and contains docstrings and comments in English. |
|
|
|
## Dataset Structure |
|
|
|
### Data Instances |
|
|
|
[More Information Needed] |
|
|
|
### Data Fields |
|
|
|
- `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`. |
|
|
|
|
|
### Data Splits |
|
|
|
The dataset only has a test split. |
|
|
|
## Dataset Creation |
|
|
|
### Curation Rationale |
|
|
|
[More Information Needed] |
|
|
|
### Source Data |
|
|
|
#### Initial Data Collection and Normalization |
|
|
|
[More Information Needed] |
|
|
|
#### Who are the source language producers? |
|
|
|
[More Information Needed] |
|
|
|
### Annotations |
|
|
|
#### Annotation process |
|
|
|
[More Information Needed] |
|
|
|
#### Who are the annotators? |
|
|
|
[More Information Needed] |
|
|
|
### Personal and Sensitive Information |
|
|
|
[More Information Needed] |
|
|
|
## Considerations for Using the Data |
|
|
|
### Social Impact of Dataset |
|
|
|
[More Information Needed] |
|
|
|
### Discussion of Biases |
|
|
|
[More Information Needed] |
|
|
|
### Other Known Limitations |
|
|
|
[More Information Needed] |
|
|
|
## Additional Information |
|
|
|
### Dataset Curators |
|
|
|
[More Information Needed] |
|
|
|
### Licensing Information |
|
|
|
[More Information Needed] |
|
|
|
### Citation Information |
|
|
|
``` |
|
@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} |
|
} |
|
``` |
|
|
|
### Contributions |
|
|
|
[More Information Needed] |
