AI-Generated Code Compliance

Why AI-Generated Code Requires Careful Auditing?

AI code generation assistants are degrading code quality:

  • Coding standards are not consistently enforced.
  • It increases duplicated code. AI is less likely to suggest reusing similar functions elsewhere in the code, partly due to limited context size.
  • It reduces refactoring. AI still struggles to consolidate previous work into reusable and maintainable modules.

Ensuring Quality and Security in AI-Generated .NET Code with NDepend

NDepend enables developers to integrate AI-generated code while maintaining strict quality and security standards.

The tool executes NDepend rules, and consolidates Roslyn Analyzers, and Resharper code inspections results obtained on AI-generated .NET code.

The NDepend's Quality Gate strategy is then applied, ensuring strict code quality enforcement. A quality gate acts as an automated and objective goal for ensuring high code quality, whether for manually written or AI-generated code. Before deployment—and ideally before committing to source control—these quality goals must be met.

Common Quality Gates enforced by NDepend include:

Finally, integrating NDepend into your CI/CD pipeline is essential. With Web Report generation, the Azure DevOps extension, or the GitHub Action, you can continuously enforce rules and validate quality gates for both manually written and AI-generated code.