README.md

---
license: apache-2.0
task_categories:
- text-generation
language:
- en
tags:
- code
- docker
- testing
- repositories
- github
- code-generation
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: java_all
    path: data/java_all-*
  - split: java_eval
    path: data/java_eval-*
  - split: java_large
    path: data/java_large-*
  - split: java_medium
    path: data/java_medium-*
  - split: java_small
    path: data/java_small-*
  - split: nodejs_all
    path: data/nodejs_all-*
  - split: nodejs_eval
    path: data/nodejs_eval-*
  - split: nodejs_large
    path: data/nodejs_large-*
  - split: nodejs_medium
    path: data/nodejs_medium-*
  - split: nodejs_small
    path: data/nodejs_small-*
  - split: python_all
    path: data/python_all-*
  - split: python_eval
    path: data/python_eval-*
  - split: python_large
    path: data/python_large-*
  - split: python_medium
    path: data/python_medium-*
  - split: python_small
    path: data/python_small-*
  - split: rust_all
    path: data/rust_all-*
  - split: rust_eval
    path: data/rust_eval-*
  - split: rust_large
    path: data/rust_large-*
  - split: rust_medium
    path: data/rust_medium-*
  - split: rust_small
    path: data/rust_small-*
  - split: python_l1
    path: data/python_l1-*
  - split: python_l2
    path: data/python_l2-*
  - split: python_l3
    path: data/python_l3-*
  - split: python_claude
    path: data/python_claude-*
  - split: python_claude_continue
    path: data/python_claude_continue-*
dataset_info:
  features:
  - name: full_name
    dtype: string
  - name: clone_url
    dtype: string
  - name: default_branch
    dtype: string
  - name: stargazers_count
    dtype: int64
  - name: language
    dtype: string
  - name: description
    dtype: string
  - name: html_url
    dtype: string
  - name: forks_count
    dtype: int64
  - name: topics
    list: string
  - name: total_bytes
    dtype: int64
  - name: code_bytes
    dtype: int64
  - name: size
    dtype: string
  - name: id
    dtype: string
  - name: language_breakdown_json
    dtype: string
  splits:
  - name: java_all
    num_bytes: 203687
    num_examples: 500
  - name: java_eval
    num_bytes: 60990
    num_examples: 150
  - name: java_large
    num_bytes: 38573
    num_examples: 80
  - name: java_medium
    num_bytes: 69081
    num_examples: 178
  - name: java_small
    num_bytes: 97012
    num_examples: 242
  - name: nodejs_all
    num_bytes: 197947
    num_examples: 500
  - name: nodejs_eval
    num_bytes: 60204
    num_examples: 150
  - name: nodejs_large
    num_bytes: 9239
    num_examples: 21
  - name: nodejs_medium
    num_bytes: 37669
    num_examples: 86
  - name: nodejs_small
    num_bytes: 151999
    num_examples: 393
  - name: python_all
    num_bytes: 214928
    num_examples: 500
  - name: python_eval
    num_bytes: 62216
    num_examples: 150
  - name: python_large
    num_bytes: 29049
    num_examples: 52
  - name: python_medium
    num_bytes: 81759
    num_examples: 190
  - name: python_small
    num_bytes: 105139
    num_examples: 258
  - name: rust_all
    num_bytes: 177941
    num_examples: 500
  - name: rust_eval
    num_bytes: 54279
    num_examples: 150
  - name: rust_large
    num_bytes: 19649
    num_examples: 44
  - name: rust_medium
    num_bytes: 73401
    num_examples: 199
  - name: rust_small
    num_bytes: 85927
    num_examples: 257
  - name: python_l1
    num_bytes: 22090
    num_examples: 50
  - name: python_l2
    num_bytes: 19338
    num_examples: 50
  - name: python_l3
    num_bytes: 19584
    num_examples: 50
  - name: python_claude
    num_bytes: 12251
    num_examples: 30
  - name: python_claude_continue
    num_bytes: 3998
    num_examples: 9
  download_size: 1202140
  dataset_size: 1907950
---

# RAT-bench: RunAnyThing Benchmark

## Dataset Summary

RAT-bench is a curated collection of GitHub repositories across multiple programming languages (Python, Java, Rust, Node.js), 
each containing Dockerfiles and unit tests. This dataset is designed for evaluating code analysis, Docker containerization, 
and automated testing capabilities.

The dataset is organized by programming language and repository size, providing 16 different configurations 
for flexible use in various research and development scenarios.

## Dataset Configurations

The dataset contains 16 configurations organized by language and size:

| Configuration | Language | Size Category | Count | Size Range | Avg Size |
|--------------|----------|---------------|-------|------------|----------|
| `python_small` | Python | Small | 258 | < 500 KB | 185 KB |
| `python_medium` | Python | Medium | 190 | 500 KB - 5 MB | 2 MB |
| `python_large` | Python | Large | 52 | > 5 MB | 25 MB |
| `python_all` | Python | All | 500 | All sizes | - |
| `java_small` | Java | Small | 242 | < 500 KB | 159 KB |
| `java_medium` | Java | Medium | 178 | 500 KB - 5 MB | 2 MB |
| `java_large` | Java | Large | 80 | > 5 MB | 103 MB |
| `java_all` | Java | All | 500 | All sizes | - |
| `rust_small` | Rust | Small | 257 | < 500 KB | 199 KB |
| `rust_medium` | Rust | Medium | 199 | 500 KB - 5 MB | 2 MB |
| `rust_large` | Rust | Large | 44 | > 5 MB | 17 MB |
| `rust_all` | Rust | All | 500 | All sizes | - |
| `nodejs_small` | Nodejs | Small | 393 | < 500 KB | 112 KB |
| `nodejs_medium` | Nodejs | Medium | 86 | 500 KB - 5 MB | 2 MB |
| `nodejs_large` | Nodejs | Large | 21 | > 5 MB | 31 MB |
| `nodejs_all` | Nodejs | All | 500 | All sizes | - |
| `python-l1_small` | Python-l1 | Small | 0 | - | - |
| `python-l1_medium` | Python-l1 | Medium | 0 | - | - |
| `python-l1_large` | Python-l1 | Large | 0 | - | - |
| `python-l1_all` | Python-l1 | All | 0 | All sizes | - |
| `python-l2_small` | Python-l2 | Small | 0 | - | - |
| `python-l2_medium` | Python-l2 | Medium | 0 | - | - |
| `python-l2_large` | Python-l2 | Large | 0 | - | - |
| `python-l2_all` | Python-l2 | All | 0 | All sizes | - |
| `python-l3_small` | Python-l3 | Small | 0 | - | - |
| `python-l3_medium` | Python-l3 | Medium | 0 | - | - |
| `python-l3_large` | Python-l3 | Large | 0 | - | - |
| `python-l3_all` | Python-l3 | All | 0 | All sizes | - |

## Usage

### Load a specific configuration

```python
from datasets import load_dataset

# Load Python small repositories (< 500 KB)
dataset = load_dataset("gemelom/RAT-bench", "python_small")

# Load Java medium repositories (500 KB - 5 MB)
dataset = load_dataset("gemelom/RAT-bench", "java_medium")

# Load all Rust repositories
dataset = load_dataset("gemelom/RAT-bench", "rust_all")
```

### Load multiple configurations

```python
from datasets import load_dataset, concatenate_datasets

# Load all small repositories across all languages
small_repos = concatenate_datasets([
    load_dataset("gemelom/RAT-bench", f"{lang}_small")["train"]
    for lang in ["python", "java", "rust", "nodejs"]
])

print(f"Total small repositories: {len(small_repos)}")
```

### Iterate through repositories

```python
import json
dataset = load_dataset("gemelom/RAT-bench", "python_all")

for repo in dataset["train"]:
    print(f"Repository: {repo['full_name']}")
    print(f"Stars: {repo['stargazers_count']}")
    print(f"Size: {repo['total_bytes']} bytes")
    
    # Parse language breakdown from JSON string
    lang_breakdown = json.loads(repo['language_breakdown_json'])
    print(f"Languages: {lang_breakdown}")
    print("---")
```

## Data Fields

Each repository entry contains the following fields:

- `full_name` (string): Repository full name in format "owner/repo"
- `clone_url` (string): Git clone URL (HTTPS)
- `default_branch` (string): Default branch name (e.g., "main", "master")
- `stargazers_count` (int): Number of GitHub stars
- `language` (string): Primary programming language
- `description` (string, nullable): Repository description
- `html_url` (string, nullable): GitHub repository URL
- `forks_count` (int): Number of forks
- `topics` (list[string]): Repository topics/tags
- `total_bytes` (int): Total repository size in bytes (all files)
- `code_bytes` (int): Code-only size in bytes (excluding assets)
- `language_breakdown_json` (string): JSON string of language distribution percentages
  - Example: `{"Python": 95.5, "JavaScript": 3.2}`
  - Parse with `json.loads(row["language_breakdown_json"])`
- `size` (string): Size category ("small", "medium", or "large")
- `id` (string): Unique identifier (format: language-size-index)

## Dataset Statistics

### Overall Statistics

- **Total repositories**: 2,000
- **Languages**: 7 (Python, Java, Rust, Node.js)
- **Configurations**: 16 (4 languages × 4 size categories)

### Size Categories

- **Small**: < 500 KB code size
- **Medium**: 500 KB - 5 MB code size  
- **Large**: > 5 MB code size
- **All**: All repositories (small + medium + large)

## Data Collection

The repositories were collected using the GitHub Search API with the following criteria:

1. **Language-specific search**: Repositories must be primarily written in Python, Java, Rust, or JavaScript/TypeScript
2. **Dockerfile requirement**: Must contain a Dockerfile for containerization
3. **Test requirement**: Must contain unit tests (for Python: pytest)
4. **Build tool requirement**: 
   - Java: Maven (pom.xml) or Gradle (build.gradle)
   - Node.js: package.json
   - Rust: Cargo.toml
5. **Activity**: Repositories updated within the last year
6. **Popularity**: Varying star counts (10-50+ stars depending on size category)

### Collection Strategy

To ensure balanced size distribution, we used a stratified sampling approach:
- 40% small repositories (< 1MB on GitHub)
- 35% medium repositories (1-5MB on GitHub)
- 25% large repositories (> 5MB on GitHub)

Repositories are sorted by code size (ascending) to prioritize smaller, more manageable projects.

## Use Cases

This dataset is suitable for:

1. **Docker Build Automation**: Training/evaluating models to generate or fix Dockerfiles
2. **Test Execution**: Analyzing test suites and test execution patterns
3. **Code Analysis**: Multi-language code understanding and analysis
4. **Repository Characterization**: Understanding repository structure and composition
5. **CI/CD Research**: Studying containerization and testing practices
6. **Benchmark Evaluation**: Evaluating code agents, LLMs, and automated tools

## Limitations

- Only includes repositories with Dockerfiles and tests (selection bias)
- Repository metadata is a snapshot from the collection date
- Some repositories may have been updated or deleted since collection
- Size measurements are approximate (based on GitHub's language statistics API)

## Citation

If you use this dataset in your research, please cite:

```bibtex
@dataset{

}
```

## License

This dataset is released under the Apache 2.0 License. Note that individual repositories 
may have their own licenses - please check each repository's license before use.

## Acknowledgments

Data collected from GitHub using the GitHub API. Repository metadata is provided by GitHub, Inc.