Inspiration

As developers, debugging and understanding errors can be time-consuming. BugLens was inspired by the need for a smarter way to track, analyze, and understand code errors — giving developers a personal AI assistant for debugging and learning from their mistakes.


What it does

BugLens allows developers to:

Submit errors and related code snippets for AI analysis.

Get AI-powered explanations and solutions for their errors.

Track and view error history, making it easy to learn from past mistakes.

Organize error reports by project, date, or type.

Essentially, it’s like having an AI pair-programmer focused on debugging.


How we built it

ASP.NET Core 9.0 for the backend API

Entity Framework Core + MySQL on Railway for storing errors and user history

AI Integration to analyze submitted errors and provide suggestions

JWT Authentication & OAuth for secure developer login

Modular Service Architecture for clean, maintainable code


Challenges we ran into

Parsing and storing complex code snippets in the database

Handling concurrent AI analysis requests efficiently

Designing a user-friendly interface for error submission and history

Managing secrets safely, especially OAuth keys, with GitHub push protection

Accomplishments that we're proud of

Fully functional AI-driven error analyzer

Complete error history tracking for each developer

Secure login with email/password and OAuth

Modular architecture ready for scaling to multiple projects and users


What we learned

Best practices for storing and retrieving code snippets

How to integrate AI analysis in a backend service

Managing user authentication securely with JWT and OAuth

Handling database migrations and cloud deployment on Railway


What's next for BugLens

Add real-time AI suggestions as developers type code

Implement project-specific dashboards for easier error tracking

Expand AI capabilities to suggest fixes, not just explain errors

Add team collaboration features to share error history among developers

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