Datasets:

Multilinguality:
multilingual
Size Categories:
100K<n<1M
Language Creators:
found
Source Datasets:
original
ArXiv:
Tags:
code
License:
repobench-c / README.md
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metadata
language_creators:
  - found
license:
  - cc-by-nc-nd-4.0
multilinguality:
  - multilingual
pretty_name: RepoBench-Completion
source_datasets:
  - original
task_categories:
  - text-generation
task_ids:
  - document-retrieval
tags:
  - code
size_categories:
  - 100K<n<1M

Dataset Card for RepoBench-C

Dataset Description

Dataset Summary

RepoBench-C (Completion) is a subtask of RepoBench(GitHub, arXiv), focuing on the prediction of the next line of code, given in-file context (including several preceding lines and import statements), and cross-file context.

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.

  • if: short for in_file, indicating the next line does not contain any cross-file module.

Supported Tasks

  • python_cff: python code prediction with cross-file-first setting.
  • python_cfr: python code prediction with cross-file-random setting.
  • python_if: python code prediction with in-file setting.
  • java_cff: java code prediction with cross-file-first setting.
  • java_cfr: java code prediction with cross-file-random setting.
  • java_if: java code prediction with in-file setting.

Loading Data

For example, if you want to load the test set to test your model on Python code prediction with cff setting, you can do the following:

from datasets import load_dataset

dataset = load_dataset("tianyang/repobench-c", "python_cff", split="test")

Note: The split argument is optional. If not provided, the entire dataset will be loaded.

Dataset Structure

{
    "repo_name": "repository name of the data point",
    "file_path": "path/to/file",
    "context": "commented and concatenated cross-file context",
    "import_statement": "all import statements in the file",
    "code": "the code for next-line prediction",
    "prompt": "cross-file context + import statements + in-file code",
    "next_line": "the next line of the code"
}

Licensing Information

CC BY-NC-ND 4.0

Citation Information

@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 for adding this dataset.