Ensure AI-generated code is production-ready
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Ensure AI-generated code is production-ready
Sonar's actionable code intelligence and AI Code Assurance capabilities ensure that all code, regardless of its origin, meets the highest quality and security standards, which is essential for building better software faster.
- Integrate with AI coding assistants, IDEs, and CI/CD pipelines
- Automatically detect AI-generated code from GitHub Copilot
- Detect bugs, vulnerabilities, and quality issues in all code
- Validate AI-generated code with AI Code Assurance
- Generate code fix suggestions in a single click with AI CodeFix
전 세계 700만 명 이상의 개발자가 신뢰하는
Code quality assurance for AI generated code
Sonar AI Code Assurance is a robust and streamlined process for validating AI-generated code through a structured and comprehensive analysis. This ensures that every new piece of code meets the highest standards of quality and security before it moves to production.
Code quality assurance for AI generated code
Sonar AI Code Assurance is a robust and streamlined process for validating AI-generated code through a structured and comprehensive analysis. This ensures that every new piece of code meets the highest standards of quality and security before it moves to production.
Fix bugs, vulnerabilities, and quality issues with a click
Sonar AI CodeFix is a powerful capability that suggests code fixes for issues discovered by our code analysis solutions SonarQube Server and SonarQube Cloud. By automating the resolution of common coding problems, Sonar AI CodeFix significantly boosts developer speed and productivity.


주요 이점
개발자의 수고를 줄이면서 AI 생성 코드의 품질과 보안을 지속적으로 개선할 수 있는 실행 가능한 코드 인텔리전스를 확보하세요.
속도 향상
DevOps 파이프라인에서 AI 코딩 문제를 해결하여 출시 주기를 가속화하고 시장 출시 시간을 단축하세요.
고품질
빌드 및 테스트 전에 AI 생성 코드가 높은 기준을 충족하도록 보장하여 디버깅 및 재작업 시간을 줄이세요.
안심
SonarQube를 활용한 자동화된 코드 검토를 통해 문제를 제거함으로써 생성형 AI 코드베이스에 대한 신뢰도를 구축합니다.
“Sonar helps our development team confidently make both AI-assisted and human-developed code fit for production by reviewing and establishing rules of good programming practices to achieve better code and avoid typical errors. It also assists us in gauging the code coverage for each project, allowing us to identify areas that still require testing.”
Dario Flores, Technical Quality Specialist