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🐞 BugRepro

AI-powered bug reproduction and debugging assistant that reproduces software bugs, generates patch suggestions, verifies fixes through regression testing, and produces comprehensive debugging reports.

Python Docker Status


🚀 Overview

BugRepro is an AI-powered debugging assistant designed to automate one of the most time-consuming parts of software development: reproducing, analyzing, and validating software bugs.

Instead of simply suggesting code changes, BugRepro follows a structured workflow that reproduces issues, securely executes them inside an isolated Docker sandbox, localizes failures, generates patch suggestions, validates fixes through automated regression testing, and produces detailed debugging reports.


✨ Features

🐞 Automated Bug Reproduction

  • Generates reproduction steps from issue descriptions
  • Executes reproduction automatically
  • Confirms whether the reported issue is reproducible

🐳 Secure Docker Sandbox

  • Isolated execution environment
  • No network access
  • CPU, memory, and process limits
  • Disposable containers for safer execution

🔍 Failure Localization

  • Stack trace analysis
  • Repository scanning
  • Symbol and file matching
  • Source code localization

🤖 AI Patch Generation

  • Generates unified Git diffs
  • Explains proposed fixes
  • Preserves the original repository

✅ Regression Testing

  • Applies generated patches to a temporary copy
  • Executes the project's test suite
  • Detects regressions before recommending a fix

📄 Debug Reports

Automatically generates structured reports containing:

  • Reproduction status
  • Execution logs
  • Stack traces
  • Failure analysis
  • Generated patches
  • Regression test results

🏗️ Architecture

Issue Report
      │
      ▼
AI Reproduction Generator
      │
      ▼
Docker Sandbox
      │
      ▼
Execution Verification
      │
      ▼
Failure Localization
      │
      ▼
Patch Generation
      │
      ▼
Regression Testing
      │
      ▼
Debug Report

🛠 Tech Stack

  • Python
  • Docker
  • Git
  • Pytest
  • AI / Large Language Models (LLMs)
  • Static Analysis
  • JSON
  • Unified Diff
  • Subprocess

📂 Project Structure

BugRepro/
│
├── bugrepro/
│   ├── sandbox.py
│   ├── regression.py
│   ├── repo_scan.py
│   ├── reporter.py
│   ├── patch_generator.py
│   └── ...
│
├── tests/
├── docs/
├── README.md
└── requirements.txt

⚙️ Installation

git clone https://github.com/<your-username>/BugRepro.git

cd BugRepro

pip install -r requirements.txt

For secure execution, install Docker and ensure it is running before using sandbox mode.


▶️ Usage

python main.py

or

python cli.py --issue issue.txt --repo /path/to/repository

Update the commands above if your project's entry point differs.


🔒 Security

BugRepro executes reproduction scripts inside an isolated Docker environment to reduce the risks associated with running AI-generated code.

Current safeguards include:

  • Docker-based isolation
  • Disabled network access
  • Resource limits
  • Temporary workspaces
  • Original repository protection
  • Patch verification through regression testing

🎯 Why BugRepro?

Most debugging tools stop after identifying an error.

BugRepro goes a step further by automating the complete debugging workflow:

  • Reproduce the issue
  • Verify the failure
  • Analyze the root cause
  • Generate a patch suggestion
  • Validate the fix
  • Produce a detailed debugging report

The result is a faster, safer, and more reproducible debugging process.


🚀 Future Improvements

  • AST-based repository indexing
  • Call graph analysis
  • Multi-language support
  • GitHub Actions integration
  • IDE extensions
  • Interactive web dashboard
  • Smarter repository understanding

🤝 Contributing

Contributions, feature requests, and bug reports are welcome.

If you have ideas for improving BugRepro, feel free to open an issue or submit a pull request.


⭐ Support

If you found BugRepro useful or interesting, consider giving the repository a ⭐.

Feedback, suggestions, and contributions are always appreciated.

About

AI-powered bug reproduction and debugging assistant that reproduces GitHub issues, executes them in a secure Docker sandbox, localizes failures, generates patch suggestions, validates fixes with regression testing, and produces detailed debugging reports.

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