Datasets:

helloadhavan
/

github_issues

license: mit
configs:
  - config_name: default
    data_files:
      - split: split1
        path: data/split1-*
      - split: split2
        path: data/split2-*
      - split: split3
        path: data/split3-*
      - split: split4
        path: data/split4-*
dataset_info:
  features:
    - name: repo
      dtype: string
    - name: pr_number
      dtype: int64
    - name: title
      dtype: string
    - name: body
      dtype: string
    - name: buggy_commit
      dtype: string
    - name: fix_commit
      dtype: string
    - name: buggy_distance
      dtype: int64
    - name: confidence
      dtype: string
    - name: files
      list:
        - name: filename
          dtype: string
        - name: patch
          dtype: string
        - name: additions
          dtype: int64
        - name: deletions
          dtype: int64
  splits:
    - name: split1
      num_bytes: 34024342
      num_examples: 6000
    - name: split2
      num_bytes: 31467405
      num_examples: 6000
    - name: split3
      num_bytes: 34011489
      num_examples: 6000
    - name: split4
      num_bytes: 34819671
      num_examples: 6000
  download_size: 50269862
  dataset_size: 134322907
task_categories:
  - text-generation
language:
  - en
tags:
  - code
pretty_name: Github issues dataset
size_categories:
  - 10K<n<100K

GitHub Pull Request Bug–Fix Dataset

Kaggle url

A curated, high-signal dataset of real-world software bugs and fixes collected from 25 popular open-source GitHub repositories.
Each entry corresponds to a single pull request (PR) and pairs contextual metadata with the exact code changes (unified diffs) that fixed the bug.

This dataset is designed for:

Automated program repair
Bug-fix patch generation
LLM-based code and debugging agents
Empirical software engineering research

Data collection methodology

Data was collected using the GitHub REST API and post-processed into a structured format.

To maintain quality and usefulness:

Only merged pull requests were included
Each PR must represent a bug fix or correctness change
Fixes are linked to both the buggy commit and the fix commit
Code changes are stored as unified diffs at the file level
Low-signal PRs (refactors, formatting-only changes, discussions) were filtered out
PRs without meaningful code changes were excluded

Each dataset row represents one bug–fix PR.

Dataset schema

Each entry follows the schema below:

{
  "repo": "owner/repository",
  "pr_number": 12345,
  "title": "Short description of the fix",
  "body": "Pull request description and context",
  "buggy_commit": "abcdef123456...",
  "fix_commit": "fedcba654321...",
  "buggy_distance": 12,
  "confidence": "medium",
  "files": [
    {
      "filename": "path/to/file.ext",
      "patch": "unified diff representing the fix",
      "additions": 10,
      "deletions": 2
    }
  ]
}

Field	Description
`repo`	GitHub repository containing the pull request
`pr_number`	Pull request number
`title`	Pull request title
`body`	Pull request description and discussion context
`buggy_commit`	Commit introducing or containing the bug
`fix_commit`	Commit that fixes the bug
`buggy_distance`	Number of commits between buggy and fix commits
`confidence`	Heuristic confidence level of bug–fix correctness
`files`	List of files modified by the fix
`files[].filename`	Path to the modified file
`files[].patch`	Unified diff containing the code changes
`files[].additions`	Number of lines added
`files[].deletions`	Number of lines removed

Supported languages

The dataset contains fixes across multiple programming languages, including (but not limited to):

C / C++
Python
JavaScript / TypeScript
Rust
Go
Java
Assembly (very rare)

Language distribution varies by repository.

Intended use cases

This dataset is well-suited for:

Training models to generate patches from real pull request context
Studying bug-fix patterns across large codebases
Building autonomous debugging or repair agents
Research in program repair, code synthesis, and software maintenance

It is not intended for:

Pull request classification or triage
Sentiment analysis

Limitations

The dataset reflects real-world noise from GitHub pull requests Buggy commit identification is heuristic and may be imperfect Some fixes involve refactoring or design changes rather than minimal patches No guarantee that fixes represent optimal or best-practice solutions

⚠️ Warning This dataset currently includes pull requests from 10 of the planned 25 repositories, totaling approximately 24,000 entries. The final release is expected to contain ~50,000 entries and occupy ~2 GB of storage.