Metabob detects, explains, and fixes coding problems created by humans and AI
Available on:
Supported languages:
GNN detects and classifies problematic code with contextual understanding
Problematic code along with enriched context is stored in Metabob's backend
The stored information from the backend is passed to an integrated LLM
The LLM generates a context-sensitive problem explanation and resolution
Metabob’s AI is trained on millions of bug fixes performed by experienced developers, allowing it to learn the root causes of many context-based problems.
These are problems traditional static code analysis tools can’t detect.
Metabob detects hundreds of logical problems, varying from race conditions to unhandled edge cases.
Integrate to analyze each pull request to improve code quality, reliability and software security by fixing problems before you merge. No CI setup required.
Replaces:
SonarQube, Deepsource, Code Climate, Codacy.
Prevent known security vulnerabilities before merging to stay compliant with software security industry standards.
Standards list:
SANS/CWE top 25, OWASP top 10, MITRE CWE.
Present top features:
- Minimal false positive rate (< 5%)
- Security gate integration
- Secrets scanning
Replaces:
Checkmarx, Snyk Code, Veracode, Semgrep, Sonarqube, Veracode, WhiteSource
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.
Get actionable insights about your project’s code quality and reliability, along with a bird’s eye view of your team’s productivity.
Key metrics:
- Overall code quality
- Code quality on a developer basis
- Most frequent problems in a codebase by category
- Estimated time to complete tasks (learn more)
Metabob can be deployed on-prem on your organization’s private cloud and customized to detect problems that are the most relevant to your team.
such as Sonarqube and linters
After analyzing the whole codebase, Metabob uses generative AI to facilitate code review and improve software security
Error type:
App unable to start new threads after run period
Error type:
Data is overrepresented in certain batches
Error type:
App using 100% available CPU on certain setups
Detect and learn the root causes of software bugs and software security vulnerabilities.
Get actionable development productivity and code quality key performance metrics.
Use Metabob's refactoring suggestions to improve code quality and maintainability.
Don't take our word for it, take theirs.
Schedule a demo, and one of our executive team members will walk you through the product!