Datasets:
Tasks:
Text Retrieval
Modalities:
Text
Sub-tasks:
document-retrieval
Languages:
code
Size:
100K - 1M
ArXiv:
License:
File size: 4,289 Bytes
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---
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)
- [Dataset Curators](#dataset-curators)
- [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 two levels of difficulty: `easy` and `hard`. Suppose the number of code snippets in the context is <math>k</math>, then for the `easy` subset, we have <math>5 \leq k < 10</math>, while for the `hard` subset, we have <math>k \geq 10</math>.
So, the specific information of each split is as follows:
<table>
<tr>
<th>subset</th>
<th>split</th>
<th>#</th>
</tr>
<tr>
<td rowspan="2">python_cff</td>
<td>easy</td>
<td>8,000</td>
</tr>
<tr>
<td>hard</td>
<td>8,000</td>
</tr>
<tr>
<td rowspan="2">python_cfr</td>
<td>easy</td>
<td>4,000</td>
</tr>
<tr>
<td>hard</td>
<td>4,000</td>
</tr>
<tr>
<td rowspan="2">java_cff</td>
<td>easy</td>
<td>8,000</td>
</tr>
<tr>
<td>hard</td>
<td>8,000</td>
</tr>
<tr>
<td rowspan="2">java_cfr</td>
<td>easy</td>
<td>4,000</td>
</tr>
<tr>
<td>hard</td>
<td>4,000</td>
</tr>
</table>
## 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
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset. |