---
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

## Table of Contents
- [Dataset Card for RepoBench-R](#dataset-card-for-repobench-r)
  - [Table of Contents](#table-of-contents)
  - [Dataset Description](#dataset-description)
    - [Dataset Summary](#dataset-summary)
    - [Supported Tasks](#supported-tasks)
  - [Dataset Structure](#dataset-structure)
  - [Dataset Creation](#dataset-creation)
    - [Curation Rationale](#curation-rationale)
    - [Source Data](#source-data)
      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
      - [Who are the source language producers?](#who-are-the-source-language-producers)
    - [Annotations](#annotations)
      - [Annotation process](#annotation-process)
      - [Who are the annotators?](#who-are-the-annotators)
    - [Personal and Sensitive Information](#personal-and-sensitive-information)
  - [Considerations for Using the Data](#considerations-for-using-the-data)
    - [Social Impact of Dataset](#social-impact-of-dataset)
    - [Discussion of Biases](#discussion-of-biases)
    - [Other Known Limitations](#other-known-limitations)
  - [Additional Information](#additional-information)
    - [Licensing Information](#licensing-information)
    - [Citation Information](#citation-information)
    - [Contributions](#contributions)

## Dataset Description

- **Homepage:** https://github.com/Leolty/repobench
- **Paper:** https://arxiv.org/abs/2306.03091

### Dataset Summary

RepoBench-R is a subtask of [RepoBench](https://github.com/Leolty/repobench), targeting the retrieval component of a repository-level auto-completion
system, focusing on extracting the most relevant code snippet from a project repository for next-line
code prediction. 

### Supported Tasks 

The dataset supports two programming languages, Python and Java, and contains two settings:

- `cff`: short for `cross_file_first`, where the cross-file module in next line is first used in the current file.
- `cfr`: short for `cross_file_random`, where the cross-file module in next line is not first used in the current file.

For each setting, we provide `train` and `test` subset, and each subset with two levels of difficulty: `easy` and `hard`. 

Suppose the number of code snippets in the context is \\(k\\), 

- For the `easy` subset, we have \\(5 \leq k < 10\\).
- For the `hard` subset, we have \\(k \geq 10\\).


## Dataset Structure



## 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


### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.