Software engineers and developers looking to adapt their code review processes in the age of AI-generated code.
Uncle Bob questions the value of human code review, suggesting AI handles it. He focuses on metrics like test coverage and complexity.
The speaker shares experience with SonarQube used before merging pull requests, highlighting the importance of automated code analysis.
The speaker agrees with Uncle Bob, noting the trend of developers becoming AI code auditors rather than manual reviewers.
Reports show a significant increase in AI-generated code, shifting focus from manual coding to auditing AI outputs.
With AI generating much of the code, the focus shifts from code style to objective, automated tests and metrics.
Cyclomatic complexity measures paths in a function. High complexity, often from AI, can be flagged by CI tools.
Combining test coverage with mutation testing ensures tests are robust and catch potential bugs missed by standard tests.
Limiting module size and analyzing dependency structures prevents large 'god files' and circular dependencies.