Datasets:
Tasks:
Text Retrieval
Sub-tasks:
document-retrieval
Languages:
code
Multilinguality:
multilingual
Language Creators:
found
Source Datasets:
original
ArXiv:
Tags:
License:
| language_creators: | |
| - found | |
| language: | |
| - code | |
| license: | |
| - cc-by-nc-nd-4.0 | |
| multilinguality: | |
| - multilingual | |
| pretty_name: RepoBench-Retrieval | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - text-retrieval | |
| task_ids: | |
| - document-retrieval | |
| # Dataset Card for RepoBench-R | |
| ## Dataset Description | |
| - **Homepage:** https://github.com/Leolty/repobench | |
| - **Paper:** https://arxiv.org/abs/2306.03091 | |
| ## Dataset Summary | |
| **RepoBench-R (Retrieval)** is a subtask of **RepoBench**([GitHub](https://github.com/Leolty/repobench), [arXiv](https://arxiv.org/abs/2306.03091)), targeting the retrieval component of a repository-level auto-completion system, focusing on retrieving the most relevant code snippet from a project repository for next-line | |
| code prediction. | |
| ## Settings | |
| - `cff`: short for cross_file_first, indicating the cross-file module in next line is first used in the current file. | |
| - `cfr`: short for cross_file_random, indicating the cross-file module in next line is not first used in the current file. | |
| ## Supported Tasks | |
| The dataset has 4 subsets: | |
| - `python_cff`: python dataset with `cff` setting. | |
| - `python_cfr`: python dataset with `cfr` setting. | |
| - `java_cff`: java dataset with `cff` setting. | |
| - `java_cfr`: java dataset with `cfr` setting. | |
| Each subset has 4 splits: | |
| - `train_easy`: training set with easy difficulty, where the number of code snippets in the context \\(k\\) satisfies \\( 5 \leq k < 10 \\). | |
| - `train_hard`: training set with hard difficulty, where the number of code snippets in the context \\(k\\) satisfies \\( k \geq 10 \\). | |
| - `test_easy`: testing set with easy difficulty. | |
| - `test_hard`: testing set with hard difficulty. | |
| ## Loading Data | |
| For example, if you want to load the `test` `cross_file_first` `python` dataset with `easy` difficulty, you can use the following code: | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("tianyang/repobench-r", "python_cff", split="test_easy") | |
| ``` | |
| > Note: The `split` argument is optional. If not provided, the entire dataset (including, train and test data with easy and hard level) will be loaded. | |
| ## Dataset Structure | |
| ```json | |
| { | |
| "repo_name": "repository name of the data point", | |
| "file_path": "path/to/file", | |
| "context": [ | |
| "snippet 1", | |
| "snippet 2", | |
| // ... | |
| "snippet k" | |
| ], | |
| "import_statement": "all import statements in the file", | |
| "gold_snippet_idex": 2, // the index of the gold snippet in the context list, 0~k-1 | |
| "code": "the code for next-line prediction", | |
| "next_line": "the next line of the code" | |
| } | |
| ``` | |
| ## Licensing Information | |
| CC BY-NC-ND 4.0 | |
| ## Citation Information | |
| ```bibtex | |
| @misc{liu2023repobench, | |
| title={RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems}, | |
| author={Tianyang Liu and Canwen Xu and Julian McAuley}, | |
| year={2023}, | |
| eprint={2306.03091}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL} | |
| } | |
| ``` | |
| ## Contributions | |
| Thanks to [@Leolty](https://github.com/Leolty) for adding this dataset. |