Code Review and Refactoring 101
A comprehensive series on building and maintaining high-quality TypeScript microservices through effective code review practices and systematic refactoring techniques.
Series Overview
This series is based on my practical experience building and maintaining production TypeScript microservices handling millions of requests daily. Each part covers essential skills for writing maintainable, testable, and scalable code.
Target Audience: Developers working with TypeScript microservices who want to improve code quality, establish better review processes, and master refactoring techniques.
What You'll Learn
Code Quality Principles: Readability, single responsibility, explicit dependencies, and fail-fast patterns
Code Review Process: How to give and receive effective feedback, what to look for, and building a review culture
Refactoring Techniques: Extract method/class, polymorphism, parameter objects, and eliminating code smells
Testing Strategies: Characterization tests, test-driven refactoring, and maintaining test coverage
Automation: ESLint, Prettier, TypeScript strict mode, CI/CD pipelines, and quality metrics
Series Structure
Topics Covered:
Why code review and refactoring matter in production systems
Core principles: readability, single responsibility, fail-fast, explicit dependencies
The refactoring mindset: when to refactor and when not to
Setting up for success: culture, metrics, and tools
Real-world example: refactoring a notification service
Key Takeaway: Code quality isn't about clever code—it's about code that's easy to understand, modify, and test.
Topics Covered:
Pull request workflow and size guidelines
What to look for: correctness, error handling, security, performance, testing
Giving effective feedback with specific examples
Receiving feedback gracefully
Building a productive review culture
Real code review examples from production services
Key Takeaway: Effective code review combines technical rigor with empathetic communication.
Topics Covered:
Extract Method: Breaking down complex functions
Extract Class: Separating responsibilities
Replace Conditional with Polymorphism: Strategy pattern for variations
Introduce Parameter Object: Grouping related parameters
Replace Magic Numbers: Using named constants
Null Object Pattern: Eliminating null checks
Complete real-world example: refactoring inventory service
Key Takeaway: Systematic refactoring patterns transform messy code into well-organized, maintainable systems.
Topics Covered:
Characterization tests for legacy code
The testing pyramid: unit, integration, E2E
Test structure: Arrange-Act-Assert pattern
Testing error paths and edge cases
Test helpers and factories
Integration testing strategies
Test-driven refactoring workflow
Key Takeaway: Tests are the safety net that makes confident refactoring possible.
Topics Covered:
ESLint configuration for TypeScript microservices
Prettier for consistent formatting
TypeScript strict mode
Pre-commit hooks with Husky
GitHub Actions CI/CD pipeline
SonarQube quality gates
Security scanning and dependency management
Code quality metrics and dashboards
Key Takeaway: Automation ensures code quality at scale, freeing reviewers to focus on architecture and logic.
Example Application
Throughout the series, I use examples from my TypeScript microservices architecture:
Prerequisites
Intermediate TypeScript knowledge
Experience with Node.js
Basic understanding of microservices
Familiarity with Git and pull requests
Jest or similar testing framework experience
How to Use This Series
For Individual Learning
Read parts sequentially—each builds on previous concepts
Try the refactoring examples in your own codebase
Set up the tools from Part 5 in a test project
Practice giving code reviews using Part 2 guidelines
For Teams
Read Part 1-2 as a team to establish shared understanding
Agree on coding standards and review processes
Implement automation from Part 5 gradually
Use Part 3-4 as reference during code reviews
Track metrics to measure improvement
For Code Review
Use as a reference during reviews:
Part 2: What to look for checklist
Part 3: Refactoring suggestions to offer
Part 4: Testing requirements
Part 5: Automation checks
Key Principles Throughout
No Fake Scenarios: All examples come from real production code
TypeScript Focus: Modern TypeScript with strict mode
Practical Over Theoretical: Actual configurations and code
Team-Oriented: Build processes that scale across teams
Continuous Improvement: Small, consistent improvements compound
Tools and Technologies
Required:
TypeScript 5.x
Node.js 18.x or 20.x
npm or yarn
Git
Recommended:
ESLint
Prettier
Jest
Husky
VS Code (or similar IDE)
CI/CD:
GitHub Actions (examples provided)
SonarQube (optional)
Codecov (optional)
Snyk (optional)
Common Questions
Q: Should I refactor everything at once?
A: No. Refactor incrementally. Follow the boy scout rule: leave code better than you found it.
Q: What if I don't have tests?
A: Start with characterization tests (Part 4) to document current behavior before refactoring.
Q: How do I convince my team to adopt these practices?
A: Start small. Implement pre-commit hooks, then add CI checks, then build out code review processes. Show metrics improvement.
Q: Is 80% code coverage realistic?
A: Yes, but it varies by service. Critical services (auth, payment) should have 90%+. Less critical services can be 70%+.
Q: What if code reviews slow us down?
A: Keep PRs small (<400 lines), review within 24 hours, and use automation to catch simple issues. Reviews actually speed up development by catching bugs early.
Metrics to Track
Monitor these to measure improvement:
Code Quality:
Test coverage percentage
Cyclomatic complexity
Code duplication percentage
Technical debt ratio
Process:
Average PR size (lines changed)
Time to first review
Number of review cycles per PR
Time from PR to merge
Outcomes:
Production bugs per week
Time to implement features
Developer satisfaction
Onboarding time for new developers
Next Steps
Start Reading: Begin with Part 1: Foundations and Principles
Set Up Tools: Configure ESLint and Prettier in your project
Practice: Try refactoring one function using Part 3 techniques
Review Code: Apply Part 2 checklist to your next PR review
Automate: Implement CI/CD pipeline from Part 5
Real-World Impact
After implementing these practices in my microservices:
Bug reports dropped 70% after systematic refactoring
Feature development time reduced from weeks to days for similar features
Test coverage increased from 45% to 85%
Code review time decreased from 2-3 days to same-day reviews
Onboarding time for new developers reduced by 50%
Production incidents reduced by 60%
Contributing
Found an error or have a suggestion? These articles are based on real experience, and I'm always learning. Feedback welcome!
Related Topics
Architecture and Patterns: Domain-Driven Design, CQRS, Event Sourcing
Testing: Test-Driven Development, Behavior-Driven Development
DevOps: CI/CD, Infrastructure as Code, Monitoring
Team Practices: Agile, Pair Programming, Mob Programming
Author Notes
This series represents lessons learned from:
5+ years working with TypeScript microservices
Reviewing 1000+ pull requests
Refactoring legacy services handling millions of requests
Building CI/CD pipelines for 20+ microservices
Mentoring developers on code quality practices
Every example, configuration, and recommendation comes from production experience—no hypothetical scenarios.
License
This content is shared for educational purposes. Feel free to adapt these practices to your organization's needs.
Ready to improve your code quality? Start with Part 1: Foundations and Principles
Last updated