🕵️ Glitch Detective

AI-Powered Code Debugging Assistant

Every bug has a story. Glitch Detective helps you solve it.

💡 Inspiration

Debugging can be frustrating, especially for beginners who struggle to understand why their code is not working. Error messages often point to a problem without clearly explaining its cause or how to fix it.

We built Glitch Detective to make debugging more approachable by helping developers identify potential bugs, understand what went wrong, and explore possible solutions with AI-powered assistance.

🎯 What It Does

Glitch Detective is an AI-powered debugging assistant that analyzes code and helps users investigate programming errors.

• 🔍 Bug Detection: Analyzes submitted code to identify potential bugs and common programming mistakes.
• 🧠 Root-Cause Explanation: Explains why a problem may occur in beginner-friendly language.
• 🛠️ Suggested Fixes: Provides corrected code suggestions to help users resolve identified issues.
• 💻 Multi-Language Support: Supports Python, Java, JavaScript, TypeScript, and C++.
• ⚡ Simplified Debugging: Turns confusing coding problems into clearer, more actionable guidance.

🛠️ How We Built It

Glitch Detective combines a user-friendly frontend with a serverless backend and AI-powered code analysis.

• Frontend: React and TypeScript
• Backend: Vercel serverless API
• AI Integration: Google Gemini API through the @google/genai SDK
• Deployment: Vercel
• Programming Languages Supported: Python, Java, JavaScript, TypeScript, and C++

The frontend collects the code submitted by the user and sends it to the backend for analysis. The backend processes the request, uses AI to analyze the code, and returns a structured result containing the analysis and suggested corrections. A fallback mechanism helps the application handle certain temporary AI service failures.

🚧 Challenges We Faced

• Integrating AI-generated debugging results into a reliable application workflow.
• Supporting multiple programming languages with different syntax and common error patterns.
• Handling temporary AI service failures without unnecessarily interrupting the user experience.
• Presenting debugging explanations and suggested corrections in a way that is understandable to beginners.

🏆 Accomplishments We're Proud Of

• Building a working, deployed AI-powered debugging application.
• Bringing support for five programming languages into one interface.
• Combining bug explanations with suggested code corrections.
• Implementing fallback behavior for certain temporary API failures.
• Making debugging more approachable for students and developers learning to code.

📚 What We Learned

Through this project, we explored AI API integration, serverless backend development, frontend-backend communication, deployment with Vercel, and the importance of handling errors gracefully.

We also learned that useful debugging assistance requires more than identifying a suspicious line: explanations and suggested fixes should help users understand the underlying issue.

🔮 What's Next for Glitch Detective?

We hope to improve Glitch Detective with features such as:

• More accurate code analysis and correction suggestions.
• Support for additional programming languages.
• Line-by-line explanations and debugging walkthroughs.
• Code execution and testing in a secure environment.
• More comprehensive test cases to validate suggested fixes.
• A history of previous analyses so users can revisit their debugging sessions.

🌟 Why Glitch Detective?

We believe debugging should be an opportunity to learn, not a barrier to building.

Glitch Detective helps turn coding confusion into understanding—one bug at a time.

Built With

• c++
• google-gemini-api
• java
• javascript
• python
• react
• typescript
• vercel