Metabob uses Graph Neural Networks trained on millions of bug fixes to analyze code logic and context across entire repositories. Unlike LLM-based tools, it understands code behavior to detect runtime errors like race conditions, unhandled edge cases, and memory leaks that traditional static analysis misses. It integrates with IDEs and CI/CD pipelines to catch bugs early.
Metabob uses Graph Neural Networks trained on millions of real bug fixes to understand code behavior and context across entire repositories. Traditional static analysis checks syntax and style rules but misses logical errors like race conditions and unhandled edge cases that only appear at runtime. Metabob focuses on bugs that actually break your code in production.
Metabob works with Python, JavaScript, TypeScript, Java, C, and C++. The tool analyzes code logic and structure in these languages to detect bugs and provide fix recommendations.
Yes, Metabob offers a free plan for individual developers using VS Code. You get IDE integration with unlimited code analyses and no credit card required. This lets you test the tool on your projects before upgrading to paid team plans.
Metabob integrates directly into VS Code through an extension and connects to your CI/CD pipeline as a quality gate. It automatically reviews new code on pull requests and commits, catching bugs before they reach production. Enterprise deployments can be self-hosted and customized to your specific use case.
Metabob finds runtime errors including race conditions, memory leaks, unhandled edge cases, performance bottlenecks, and resource management issues. It also identifies code smells and areas needing refactoring to reduce technical debt.
Yes, unlike LLM-based tools that review code in chunks, Metabob uses graph neural networks to analyze complete repositories. It maps code structure and data flow across all modules and files to understand context, making it effective for reviewing large, complex legacy systems.
Metabob can validate code generated by AI assistants like GitHub Copilot or ChatGPT. It scans AI output for bugs, checks if the code integrates properly with your existing project, and suggests corrections before you merge it into your codebase.
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