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Metabob

Metabob

Metabob automates code reviews, improving software and developer productivity.

generative AIgraph-attention networkscode reviews
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Introduction

Metabob is a generative AI tool that uses a combination of graph-attention networks and generative AI to automate and improve code reviews. It helps detect and fix coding problems created by humans and AI, improving software security and developer productivity.

Key Features

Generative AI for code refactoring and debugging

Graph-attention networks for code review facilitation

Static code analysis for software security

Debugging code with automatically generated recommendations

Code refactoring recommendations for code quality improvement

Project metrics for code quality and team productivity evaluation

Self-hosted deployment for customization and privacy

Frequently Asked Questions

What is Metabob?

Metabob is a generative AI tool that uses a combination of graph-attention networks and generative AI to automate and improve code reviews. It helps detect and fix coding problems created by humans and AI, improving software security and developer productivity.

How to use Metabob?

To use Metabob, you can get started by installing the VS Code extension or integrating it with your GitHub, BitBucket, or GitLab repositories. Once integrated, Metabob utilizes its proprietary graph neural networks to detect problematic code, which is then passed to a large language model (LLM) to generate context-sensitive explanations and resolutions. Metabob can be used for static code analysis, debugging code, code review facilitation, and code optimization.

What programming languages does Metabob support?

Metabob supports Python, JavaScript, TypeScript, C++, C, and Java.

Can Metabob be used for software security scanning?

Yes, Metabob can detect known security vulnerabilities and help ensure compliance with industry standards such as SANS/CWE top 25, OWASP top 10, and MITRE CWE.

Is Metabob suitable for large codebases?

Yes, Metabob is capable of analyzing complete codebases and provides context-sensitive code recommendations and refactoring suggestions.

Can Metabob be deployed on-premises?

Yes, Metabob can be deployed on-premises on your organization's private cloud, allowing for customization and privacy.

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Use Cases

  • Automating and improving code reviews
  • Enhancing software security through static code analysis
  • Debugging and optimizing code performance
  • Refactoring code for better maintainability and code quality
  • Evaluating project metrics for productivity and code quality analysis

How to Use

To use Metabob, you can get started by installing the VS Code extension or integrating it with your GitHub, BitBucket, or GitLab repositories. Once integrated, Metabob utilizes its proprietary graph neural networks to detect problematic code, which is then passed to a large language model (LLM) to generate context-sensitive explanations and resolutions. Metabob can be used for static code analysis, debugging code, code review facilitation, and code optimization.
Metabob: Metabob automates code reviews, improving software and developer productivity. | Review AI Tools