About This Course
Use AI coding assistants to review legacy code, uncover risks, generate tests, refactor safely, and plan modernization.
What you'll learn:
- Use AI coding assistants to support structured, evidence-based legacy-code review.
- Establish a runnable baseline before changing an inherited application.
- Summarize unfamiliar codebases and trace standard and cross-cutting workflows.
- Identify hidden business rules, role assumptions, validation behavior, and undocumented dependencies.
- Separate verified evidence from AI-generated assumptions and recommendations.
- Build a technical debt and risk register with impact, severity, confidence, and recommended action.
- Build a technical debt and risk register with impact, severity, confidence, and recommended action.
- Generate and critically review characterization, unit, integration, and manual validation scenarios.
- Refactor small code seams safely and decide when a controlled rewrite is more appropriate.
- Prepare clear pull request summaries, reviewer notes, and reusable review packages.
- Validate changes through source inspection, builds, tests, runtime behavior, and diff review.
- Adapt the workflow to other languages, frameworks, repositories, and AI development tools.