Best Practices for Successful Refactoring
Identifying code that could be refactored is easy. Deciding if you should refactor it is not.
👋 Hi, this is Thomas, with a new issue of “Beyond Code: System Design and More”, where I geek out on all things system design, software architecture, distributed systems and… well, more.
QUOTE OF THE WEEK:
Getting distributed systems right--performance, reliability, scalability, whatever "right" means--is hard. - Loosely paraphrased from A Note on Distributed Computing
Almost every codebase has parts that could be refactored. In fact, spotting code that needs refactoring is rarely the hard part—it usually waves at you with a broken test and a cryptic error message.
But should you refactor them? That’s not always obvious. With limited time, complexity creeping in, and competing priorities, knowing when to refactor—and when to leave things alone—is a skill.
Implementing effective code refactoring requires a structured approach that balances improvement goals with practical constraints. Here are some best practices:
Incremental Implementation
Rather than attempting large-scale overhauls, adopt an incremental approach to refactoring. This strategy allows teams to make progressive improvements while maintaining system stability. Small, focused changes reduce risk and integrate smoothly with existing development workflows. Teams can tackle technical debt systematically while continuing to deliver new features.
Comprehensive Testing Strategy
Automated testing forms the foundation of safe refactoring. Implement a robust testing framework that includes (at the very least):
Unit tests to verify individual components, functions, methods, or classes in isolation.
Integration tests to validate that multiple components of the system work together as expected
End-to-end (E2E) tests to simulate real-world workflows and ensure that the entire application works correctly from start to finish.
Clear Communication Protocols
Major refactoring efforts require clear communication across the organization. Establish processes for:
Documenting architectural decisions and their rationale (see this software design document template as inspiration)
Conducting regular code reviews
Sharing progress updates with stakeholders
Coordinating changes across development teams
Leveraging Development Tools
Modern development tools can significantly enhance refactoring efficiency. Utilize:
Static analysis tools to examine code to identify issues like code smells, syntax errors, or potential bugs.
IDE feedback and linting tools to enforce consistent code style across the team by identifying and fixing formatting issues.
Security analysis tools detect vulnerabilities and highlight insecure code patterns.
Visualization tools to understand your system architecture and gather insights into system dependencies and structure.
Architectural Considerations
If your app is buckling under heavy traffic or you've accumulated a lot of architectural technical debt, small fixes won’t cut it. When performance, scalability, or long-term maintainability start to suffer due to deeper structural issues, it might be time for an architectural refactor.
This means stepping back and rethinking how your system is designed, and considering bigger shifts: e.g. like breaking up a monolith into microservices, adding caching layers, or enabling horizontal scaling.
I originally wrote about this topic in this article:
I explored these topics:
Determine what code to refactor
Perform code refactoring incrementally
Consider architectural refactoring
Write automated tests to refactor safely
Communicate major changes throughout the organization
Leverage existing tools for effective code refactoring
📚 Interesting Articles & Resources
Beyond Buzzwords: Embedding Real Shift-Left Practices - by
This article revisits the concept of "shift left testing," emphasizing its longstanding presence since the early 2000s. Moreira advocates for integrating testing discussions early in the development process by embedding QA professionals within development teams. Short, focused sessions between developers and testers can prevent redundant efforts, foster trust, and leverage diverse testing strategies.
Is vibe coding the future of Software Engineering? - by
We’ve all heard of "vibe coding" to some degree by now: a method where developers use natural language prompts to instruct AI models to generate code. For those who haven’t tried it and are looking for a practical example, this article offers a straightforward example by building a newsletter page clone using Cursor. In my opinion vibe coding will be a huge productivity booster, but a solid grasp of engineering principles remains essential for software design, debugging and security.
You Don’t Know Everything, and That Is Okay - by Pavan Policherla
It's impossible to know everything in the tech industry—and that's ok. Instead of striving for complete knowledge, the focus should be on problem-solving skills and continuous learning. Leveraging available resources, effective teamwork and a willingness to learn are more valuable than attempting to master every new technology.