We spend a lot of time talking about “code quality”. Ask ten developers what it means, and you’ll get ten different answers: low bug rate, consistent style, high unit test coverage, SOLID principles, low cyclomatic complexity, or maybe just “code that makes me feel good when I look at it”, but when you boil it all down, there’s only one measure of quality that really matters: how easily we can change the code tomorrow.

Everything else - readability, test coverage, architecture, even naming conventions—only matters in so far as it increases (or decreases) our ability to adapt the codebase when reality inevitably changes.

Table Of Contents

Why change is the real measure#

Software doesn’t live in a vacuum. Requirements shift, features evolve, teams grow, and mistakes need fixing. The one constant is change. If your code is “beautiful” but rigid, it’s a liability. If it’s ugly but malleable, it’s an asset.

Think about it:

  • A clever one-liner might impress your peers, but if nobody can understand or safely refactor it six months later, is it really high quality?
  • A 90% test coverage report looks great on paper, but if the tests are brittle and block every small refactor, they’re hurting change, not helping it.
  • Strict adherence to patterns can feel disciplined, but if they’re applied dogmatically, they can trap you in a maze of abstractions that makes change harder, not easier.

The illusion of secondary metrics#

We latch onto metrics because they’re easy to measure: linting, test coverage, code churn, static analysis scores. But these are proxies, not the end goal. They can give us signals, but none of them guarantee adaptability.

For example:

  • Low complexity often means easier changes—but not always. Sometimes a complex domain requires complex code, and over-simplifying it makes future changes harder.
  • Consistency in style makes change less mentally taxing—but style guides alone won’t save you from tangled dependencies.
  • Performance optimizations may be technically impressive, but if they freeze the design and prevent iteration, you’re paying the wrong price.

Designing for change#

So, how do we actually measure and design for changeability? A few guiding principles:

  1. Localize decisions – Changes should ripple as little as possible. If adding a feature forces edits across ten files in unrelated modules, your design is resisting change.
  2. Lean on tests that enable refactoring – Tests should make it safer to change code, not punish you for trying. Favor higher-level integration tests over brittle mocks.
  3. Readability is for future-you – You don’t write code for the compiler; you write it for the humans who will modify it next (likely including yourself, after you’ve forgotten everything).
  4. Avoid premature optimization and abstraction – Over-abstracted code makes small changes expensive. Over-optimized code is often calcified code.
  5. Practice continuous refactoring – Small, ongoing cleanups keep the codebase supple. Waiting until it’s “bad enough” usually means it’s already too late.

A mental shift#

When we review code, we should stop asking “Is this correct?” or “Does this look nice?” Those matter, but they’re secondary. The real question is: “If requirements change tomorrow, how painful will it be to adapt this?”

That’s the north star of code quality.

Conclusion#

Code quality is often treated like an aesthetic judgment or a scorecard of best practices. But in practice, the only thing that truly matters is changeability. Can we adapt, extend, and evolve this code without fear? If yes, the code is high quality. If not, it isn’t—no matter how elegant it looks today.

In the end, our job as developers isn’t just to write code that works. It’s to write code that keeps working, even as the world around it changes.

TODO#

go forth and nerd out