README.md

metadata

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

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

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

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:

@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.