Bugger

A Gradio-based dashboard for analyzing and categorizing Azure DevOps bugs, helping you prioritize and clean up your bug backlog.

Features

• 🤖 AI-Powered Analysis: Optional GPT-4o integration for intelligent bug categorization and actionability assessment
• Smart Fallback System: Graceful degradation to heuristic analysis when OpenAI package is unavailable
• Questionable Bug Detection: Identifies bugs with insufficient descriptions, broken references, or other issues that make them non-actionable
• Intelligent Categorization: AI-enhanced grouping of actionable bugs by type (crashes, performance, drivers, etc.)
• Azure DevOps Integration: Direct query links to view bugs in Azure DevOps
• Statistical Analysis: Shows average bug age and time in active state
• Batch Query Support: Handles large bug lists by creating batched queries
• Dual Mode Interface: Dynamic UI showing current analysis mode (AI vs heuristic)

Setup

1. Create a .env file with your Azure DevOps credentials:

AZURE_DEVOPS_ORG=your-organization
AZURE_DEVOPS_PROJECT=your-project
[email protected]
AZURE_DEVOPS_PAT=your-personal-access-token

# Optional: Enable AI-powered analysis (requires OpenAI package)
OPENAI_API_KEY=your_openai_api_key_here

How to get your Personal Access Token (PAT):

1. Go to https://dev.azure.com and sign in

2. Click on your profile picture (top right) → User settings → Personal access tokens

3. Click "New Token"

4. Give it a name and select expiration

5. Under "Scopes", select:

   • Work Items → Read
   • Project and Team → Read

6. Click "Create" and copy the token immediately (you won't see it again!)

7. Install dependencies:

pip install -r requirements.txt

Optional: Enable AI-Powered Analysis

For enhanced AI-powered bug analysis using GPT-4o:

pip install openai

Then add your OpenAI API key to the .env file. The application will automatically detect the availability of AI features and fall back to heuristic analysis if OpenAI is unavailable.

3. Run the dashboard:

python main.py

Architecture

The application is organized into modular components:

• config.py - Configuration and environment variables with optional AI detection
• azure_client.py - Azure DevOps API interactions
• bug_analyzer.py - Bug statistics calculations
• bug_categorizer.py - Actionable bug categorization
• report_generator.py - Report generation logic
• questionable_analyzer.py - Heuristic-based questionable bug detection
• ai_bug_analyzer.py - GPT-4o powered intelligent bug analysis (optional)
• main.py - Main orchestration and adaptive Gradio UI