When Should You Refactor Legacy Code? Lessons, Pitfalls, and Best Practices

Many programmers inherit legacy projects riddled with copied code, spelling errors, and fragile functions, leading to frustration when tasked with adding new features.

Happy Ending: Refactored code receives praise from teammates.

Normal Ending: After a few months, the refactored code becomes difficult to extend, prompting another rewrite.

Bad Ending: The refactored code introduces bugs, forcing emergency fixes and revealing that the original implementation had hidden reasons.

Do You Really Need to Refactor?

Before starting a refactor, ask yourself and your team, "Do we really need to refactor?" Refactoring brings no direct profit to users, who care only about product improvements, not code aesthetics. It consumes developer resources and can be a loss for the company.

Given the short lifecycle of internet products, code written today may become obsolete in a few years. Refactoring should only be considered if the project still has significant future potential.

Why Refactor a Project?

Common reasons include:

Too many bugs or poor stability, making the current framework hard to fix.

New business requirements that the existing architecture cannot satisfy.

If the project is stable and no new demanding features are planned, refactoring is not recommended.

Example: In a previous role, we migrated a bidding result storage from a database table to a RabbitMQ queue. The original design caused database deadlocks when multiple upload instances queried the same records, and it lacked flexibility for new result formats.

Refactor Project

After careful evaluation, we decided to proceed with the refactor, knowing that a series of pitfalls awaits.

Before Refactoring

The first step is to thoroughly understand the project.

A common mistake is failing to faithfully reproduce existing functionality. Over time, code evolves, and few people—including original authors—fully grasp all features, risking accidental removal of hidden functionalities.

Refactoring – Testing

Testing is the most critical first step. If the original code lacks unit or integration tests, add them before refactoring. Tests act like a mold of the old key, ensuring the new key fits perfectly.

In one case, a unit test incorrectly asserted a NULL result, which we changed to 0. This mistake caused significant output differences after deployment.

Takeaway: With proper integration tests, such errors are caught early; trust the existing test suite instead of assuming your refactored logic is correct.

Refactoring – Branches

Never delete all code at once. Instead, copy functions/files to a new location and develop the new implementation alongside the old.

Allows reference to the original code while writing new code.

Results in cleaner code reviews.

Keeps version‑control history tidy.

In the database‑to‑RabbitMQ migration, we created a new function to push results to the queue while leaving the old upload program untouched.

Refactor Launch – Switches

For larger refactors, use feature toggles to switch between old and new logic, enabling quick rollback if issues arise.

If the outcome is uncertain, implement an A/B test: route a small percentage of traffic to the new code and compare results on a monitoring platform. Gradually increase traffic if the new version performs well.

In our case, we sent 1% of bidding results to the queue, observed the new uploader’s consumption, and verified that both control and experiment groups produced comparable results.

Summary

Key takeaways: assess the necessity of refactoring, ensure comprehensive testing, use branching strategies, and employ feature toggles or A/B testing to mitigate risk during rollout.