Metabob

What is Metabob?

Metabob is an AI tool that leverages generative AI and graph-attention networks to conduct code reviews and enhance software security. It can detect, explain, and repair coding issues generated by humans and AI. Metabob also recognizes and categorizes hundreds of contextual code problems which traditional static code analysis tools might miss. It improves software security by preventing known vulnerabilities from being merged into the main codebase and is compliant with major software security industry standards such as SANS/CWE top 25, OWASP top 10, and MITRE CWE.

Metabob utilizes a Graph Neural Network with an attention mechanism to understand both semantic and relational markers for a comprehensive representation of the input. When problematic code is detected and classified, the data is stored in Metabob's backend, and a Large Language Model generates a context-sensitive problem explanation and resolution.

This tool can detect and classify various code issues like race conditions and unmanaged edge cases, providing context-sensitive code recommendations, and improving code maintainability and software security. It can be deployed on-premises, tailored to detect problems relevant to a specific team, and outperforms traditional static code analysis tools by utilizing generative AI.

Overall, Metabob assists in preventing security vulnerabilities, complies with industry standards, offers project metrics and insights into team productivity, provides refactoring recommendations, and aids in detecting and resolving software bugs and security vulnerabilities using its trained AI and advanced technology.

Who created Metabob?

Metabob was created through NECX's Accelerator Program in collaboration with NEC Labs. It was launched on May 6, 2023, aiming to solve complex coding issues with AI code review by detecting, explaining, and providing plain-text recommendations for fixing coding problems. The tool was designed to improve software security by preventing known vulnerabilities and complying with industry standards like SANS/CWE top 25, OWASP top 10, and MITRE CWE. The founders and company details are linked to NECX and NEC Labs, which were instrumental in the tool's development.

What is Metabob used for?

• Metabob can detect hundreds of contextual code problems
• Automates code review and enhances software security
• Improves code maintainability by generating context-sensitive problem explanation and resolution
• Increases developer productivity by providing context-sensitive code recommendations
• Enforces code quality with refactoring suggestions
• Detects critical errors early in the development process
• Supports multiple programming languages such as Python, JavaScript, TypeScript, C++, C, and Java
• Can be deployed on-premises on a company's private cloud
• Offers insights into project metrics and team productivity
• Prevent known security vulnerabilities by scanning codebase and comply with industry standards
• Automating code reviews
• Enhancing software security
• Detecting, explaining, and repairing coding issues generated by humans and AI
• Recognizing and categorizing contextual code problems
• Improving code maintainability
• Identifying software security vulnerabilities
• Providing actionable key performance metrics
• Increasing developer productivity
• Preventing known security vulnerabilities from being merged into the main codebase
• Customizing to meet the needs of specific teams

Who is Metabob for?

• Software developers
• Programmers
• DevOps Engineers
• Security analysts
• IT Managers
• Quality Assurance Specialists
• Developers
• Software engineers

How to use Metabob?

To use Metabob effectively, follow these steps:

1. Understanding Metabob: Metabob is an AI tool that leverages generative AI and graph-attention networks for code reviews and software security enhancement. It can detect, explain, and fix coding issues efficiently.

2. Improving Software Security: Metabob enhances software security by detecting, explaining, and suggesting fixes for code problems. It can prevent known vulnerabilities from being merged into the main codebase, complying with industry standards.

3. Generative AI and Graph-attention Networks: Metabob's proprietary Graph Neural Network with an attention mechanism helps understand semantic and relational aspects in code for accurate representations.

4. Code Issues Detection: Metabob can identify and classify various code problems, including critical errors and security vulnerabilities, providing context-specific explanations and resolutions.

5. Customization and Deployment: Metabob can be customized to suit team needs and deployed on-premises. It can be tailored to detect relevant problems, increasing productivity and code quality.

6. Comparison to Static Analysis Tools: Metabob outperforms traditional tools by utilizing generative AI for better detection of critical errors, improving developer productivity with targeted solutions.

7. Languages and Integration: Metabob supports languages like Python, Java, JavaScript, etc. It's available for VS Code, making it convenient for developers to use within their preferred IDE.

By following these steps, users can effectively utilize Metabob to improve code quality, enhance software security, and boost team productivity.