Phase 3: Code Review (순수 리뷰 로직)

Automate code review in CI/CD by running multi-round AI-driven analysis to identify and categorize issues across security, errors, data integrity, performance, and code quality. This ensures code quality gates are met before production deployment.

Multi-round AI code review is an automated process that iteratively analyzes source code to catch critical bugs. By conducting multiple passes of AI feedback, it systematically categorizes vulnerabilities and performance issues to enforce strict quality assurance standards.

Yes, you can manage and apply suppression lists during automated code analysis. This feature allows developers to intentionally ignore known or acceptable issues, ensuring the AI review process focuses strictly on new security threats and code quality regressions.

Run AI code analysis by executing the review process on your implemented codebase. The AI agents automatically categorize identified issues across specific dimensions like Security (SEC) and Data Integrity (DATA), providing targeted feedback for those critical areas.

Automated code review integrates directly with CI/CD pipelines to enforce quality gates. By running AI agents during the build process, it automatically flags high-priority bugs and security vulnerabilities before code changes are merged into production.

AI code review identifies issues across five distinct categories: Security (SEC), Errors (ERR), Data Integrity (DATA), Performance (PERF), and Code Quality (CODE). This categorized feedback helps developers prioritize fixes based on the specific nature of the vulnerability.