AI code review for refactoring and debugging

Metabob detects, explains, and fixes coding problems created by humans and AI

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Available on:

Github

Bitbucket

Gitlab

VS Code

Supported languages:

Python

Javascript

Typescript

C++

Java

Metabob raises generative AI to a new level

Metabob utilizes proprietary graph neural networks to detect problems and LLMs to explain and resolve them - combining the best of both worlds

Graph Neural Networks (GNNs) utilize an attention mechanism to comprehend both semantic & relational markers, resulting in a more complete representation of the input
Large Language Models (LLMs, such as GPT) are deep learning models that use billions of parameters & an attention mechanism to predict the most likely token to follow a given input

GNN detects and classifies problematic code with contextual understanding

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Problematic code along with enriched context is stored in Metabob's backend

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The stored information from the backend is passed to an integrated LLM

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The LLM generates a context-sensitive problem explanation and resolution

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AI Code Review

Metabob's AI is trained on millions of bug fixes performed by experienced developers. The ability to understand code logic and context, enables Metabob to detect complex problems that span across codebases and automatically generates fixes for them.

Metabob's AI code review detects hundreds of logical problems, varying from race conditions to unhandled edge cases. Such problems cannot be detected with traditional static analysis tools (e.g., Sonarqube, Deepsource).

Integrate to analyze each pull request to improve code quality, reliability and software security by fixing problems before you merge. No CI setup required.

Software Security Scanning

Before merging code, Metabob ensures that known security vulnerabilities are detected to stay compliant with software security industry standards. In addition, Metabob's AI is able to detect complex security vulnerabilities that require contextual and logical understanding of the code base.

Standards lists:
SANS/CWE top 25, OWASP top 10, MITRE CWE.

Present top features:
- Minimal false positive rate (< 5%)
- Security gate integration
- Secrets scanning

Debug and Refactor

Debug faster by automatically generated code fix recommendations and enforce code quality and best practices with Metabob’s refactoring recommendations.

Debugging
Metabob’s ability to analyze complete code bases allows it to generate context-sensitive code recommendations for found bugs and code smells.

Refactoring
Metabob enforces code quality and best practices by offering refactoring recommendations for areas with messy and ineffective code, ultimately reducing the creation of technical debt and optimizing LOC performance.

Self-hosted

Metabob can be deployed on-premise on your organization’s private cloud and customized to detect problems that are the most relevant to your team.

AI code review that outperforms
traditional static code analysis tools

such as Sonarqube and linters

After analyzing the whole codebase, Metabob uses generative AI to facilitate code review and improve software security

Increased developer productivity

Higher detection rate of critical errors

Error type:
Intermittent server crashes
‍

1.5

Hours Saved

of 2h standard debugging time

Error type:
App unable to start new threads after run period

40

Minutes Saved

of 1h standard debugging time

Error type:
Data is overrepresented in certain batches

2.5

Hours saved

of 3h standard debugging time

Error type:
App using 100% available CPU on certain setups

1.25

Hours saved

of 1.5h standard debugging time

Browse Features

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Supported Languages

Metabob is different from ChatGPT & CoPilot

Instead of generating code based on prompts, Metabob analyzes and fixes existing code

Metabob's AI automatically identifies and explains regions of code that are likely to contain specific types of issues from their structural and semantic relationships.
Metabob feeds problematic code, its explanation, and contextual information along with test cases to generative AI models.
Without user input, Metabob generates context-sensitive code recommendations to fix detected problems.