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February 9, 2024
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CodeAnt AI

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AI to detect & auto-fix bad code
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CodeAnt AI is a tool engineered to identify and automatically repair flawed code. The system can detect various issues, such as anti-patterns, duplicate or dead code, overly complex functions, security vulnerabilities and more, offering suggestions and auto-fixes for these problems.

The tool is created with the purpose to streamline developers' workflow, saving time by not only identifying but also rectifying problematic code, directly within the developers' Integrated Development Environment (IDE) and Continuous Integration (CI) systems like GitHub and BitBucket.

The AI tool also documents the entire codebase, providing visibility into the code's structure and quality over time. It can operate on both file and repository levels, offering solutions at the individual file level, as well as scanning the entire codebase for potential issues.

In addition, CodeAnt AI supports end-to-end integration with the development workflow and is designed to automatically address coding issues during pull requests, ensuring the highest code quality.

While it is primarily aimed at developers, CodeAnt AI also provides organizations with an overview of code quality across different repositories and teams.

CodeAnt AI can be deployed entirely on-prem or in Virtual Private Cloud (VPC), ensuring data safety.

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Pricing

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Free Trial
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$19/month
Billing frequency
Monthly
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CodeAnt AI was manually vetted by our editorial team and was first featured on February 9th 2024.

Pros and Cons

Pros

Auto-repairs flawed code
Detects multiple code issues
Streamlines developer workflow
IDE and CI integration
GitHub and BitBucket compatible
Full codebase documentation
Operates on file, repository levels
Handles pull request code issues
Overview of code quality
On-prem or VPC deployment
End-to-end workflow integration
Code security feature
Auto-generated code docstrings
Unit-tests generation
Bulk code fixes
Code quality analytics
Extension for VS Code, JetBrains
Auto-fixing during code development
Supports organization-level code analysis
Enforces clean coding practices
Deployed in encrypted environment
Detects, rectifies bad code
Cost-effective code debugging
Time saving for developers
Detects anti-patterns
Identifies duplicate, dead code
Recognizes complex functions
Highlights security vulnerabilities
Suggests code improvements
Automatically prompts for bad code
Reduces tech debt
Saves developer hours
Suits individual developers
Teams, repositories code quality view
Lines of code scanned
Auto-fixed anti-patterns count
Hours saved indicator
Compatible with more languages
Supports PR code checks
Proactive code issue fixing
Handles up to 200 files
Manages repository rules
Offers diagram and Docstring feature
Improves code onboarding process
Helpful in reducing tech debt
Provides security loop hole alerts
Offers efficiency, quality in one
Pinpoints inefficiencies in code
Enhances code security
Secures data within company's infrastructure

View 45 more pros

Cons

No multi-language support
Limits bulk fixes
No offline support
No integration with other IDEs
Problems with large codebases
Over-dependency on IDE integration
May produce false positives
Not optimized for small teams
No version control system integration
No freemium version for teams

View 5 more cons

7 alternatives to CodeAnt AI for Debugging

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Q&A

What exactly is CodeAnt AI?
What type of code flaws can CodeAnt AI detect?
How does CodeAnt AI integrate with my IDE and CI systems?
Does CodeAnt AI support both GitHub and BitBucket?
What does it mean when CodeAnt AI documents the entire codebase?
Can CodeAnt AI operate on both individual file and repository levels?
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