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---
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license: mit
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configs:
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- config_name: default
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data_files:
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path: data/split1-*
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- split: split2
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path: data/split2-*
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- split: split3
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path: data/split3-*
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- split: split4
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path: data/split4-*
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dataset_info:
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features:
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- name: repo
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dtype: string
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- name: issue_number
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dtype: int64
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- name: issue_title
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dtype: string
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- name: issue_body
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dtype: string
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- name: commit_sha
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dtype: string
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- name: files
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list:
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- name: filename
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dtype: string
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- name: patch
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dtype: string
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- name: additions
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dtype: int64
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- name: deletions
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dtype: int64
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splits:
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- name: split1
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num_bytes: 50886134
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num_examples: 2000
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- name: split2
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num_bytes: 53889478
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num_examples: 2000
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- name: split3
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num_bytes: 58002025
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num_examples: 2000
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- name: split4
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num_bytes: 52200575
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num_examples: 1984
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download_size: 210310215
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dataset_size: 214978212
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---
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license: mit
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| 3 |
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configs:
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| 4 |
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- config_name: default
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| 5 |
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data_files:
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- split: split1
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path: data/split1-*
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- split: split2
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path: data/split2-*
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- split: split3
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path: data/split3-*
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- split: split4
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path: data/split4-*
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dataset_info:
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features:
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- name: repo
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dtype: string
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- name: issue_number
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dtype: int64
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- name: issue_title
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dtype: string
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- name: issue_body
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dtype: string
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- name: commit_sha
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dtype: string
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- name: files
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list:
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- name: filename
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dtype: string
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- name: patch
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dtype: string
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- name: additions
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dtype: int64
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- name: deletions
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dtype: int64
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splits:
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- name: split1
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num_bytes: 50886134
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num_examples: 2000
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- name: split2
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num_bytes: 53889478
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num_examples: 2000
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- name: split3
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num_bytes: 58002025
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num_examples: 2000
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- name: split4
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num_bytes: 52200575
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num_examples: 1984
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download_size: 210310215
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dataset_size: 214978212
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task_categories:
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- text-generation
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language:
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- en
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tags:
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- code
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pretty_name: Github issues dataset
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size_categories:
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- 1K<n<10K
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---
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# GitHub Issues + Fixes Dataset
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A **curated, high-signal dataset** of GitHub issues collected from **25 popular open-source repositories**.
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Each example pairs a real GitHub issue with the **exact code changes (diffs)** that resolved it.
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The dataset is designed for:
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- **Automated bug fixing**
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- **LLM-based code agents**
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- **Issue → patch generation**
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- **Program repair research**
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---
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## How the data was extracted
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The data was collected using the **GitHub REST API** and processed into a structured format.
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To maintain quality and usefulness:
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- Only **closed issues** were considered
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- Each issue must have a **clearly associated fix**
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- Fixes are stored as **unified diffs** extracted from the resolving commit
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- Low-signal issues (questions, duplicates, discussions) were filtered out
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- Issues without meaningful code changes were excluded
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Each row represents **one issue–fix pair**.
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---
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## Dataset structure
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Each dataset entry has the following schema:
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```json
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{
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"repo": "owner/repository",
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"issue_number": 12345,
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"issue_title": "Short description of the problem",
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"issue_body": "Full issue discussion and problem description",
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"commit_sha": "abcdef123456...",
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"files": [
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{
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"filename": "path/to/file.ext",
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"patch": "unified diff showing the fix",
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"additions": 10,
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"deletions": 2
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}
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]
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}
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```
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| Field | Description |
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| ------------------- | -------------------------------------------- |
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| `repo` | GitHub repository where the issue originated |
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| `issue_number` | Original GitHub issue number |
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| `issue_title` | Title of the issue |
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| `issue_body` | Full issue description and context |
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| `commit_sha` | Commit that fixed the issue |
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| `files` | List of modified files |
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| `files[].filename` | Path of the modified file |
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| `files[].patch` | Unified diff representing the fix |
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| `files[].additions` | Number of added lines |
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| `files[].deletions` | Number of removed lines |
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## Supported languages
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The dataset contains fixes across multiple programming languages, including (but not limited to):
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* C / C++
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* Python
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* JavaScript / TypeScript
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* Rust
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* Go
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* Java
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* Assembly
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Language distribution varies by repository.
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## Intended use cases
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This dataset is well-suited for:
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* Training models to generate code patches from issue descriptions
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* Evaluating LLM reasoning over real-world bug reports
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* Building autonomous debugging or refactoring agents
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* Research on program repair, code synthesis, and software maintenance
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It is **not** intended for:
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* Issue classification
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* entiment analysis
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* Chatbot fine-tuning without code generation
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## Limitations
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* The dataset reflects real-world noise from GitHub issues
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* Issue descriptions vary widely in clarity and detail
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* Some fixes involve refactoring or design changes rather than minimal patches
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* No guarantee that all fixes are optimal or best practice
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> **<span style="color:red;font-size:1.25rem">Warning</span>**: This dataset currently has the issues if 9/25 repos and 8k rows but is expected to have 50k rows and 2 GB in size
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