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11 Common Code Smells and How to Fix Them in 2025 [LATEST]

Amartya Jha

• 8 June 2025

Content

If you've ever opened a file and instantly felt uneasy, like something’s off, even if it “works,” you’ve already experienced a code smell.

It’s that moment when a method feels way too long. Or when one change means touching six files. Or when you're scared to refactor because no one really knows how this thing still runs in prod.

Code smells aren’t bugs. They won’t crash your app. But they’re warning signs. Clues that the code beneath might be harder to understand, extend, or debug later. And the more your project grows, the more these smells pile up, until even the smallest task feels risky.

That’s why clean code isn’t just about writing “beautiful” code. It’s about writing survivable code. Code that plays well with teammates, makes sense months later, and doesn’t break when you blink at it wrong.

In this guide, we’ll break down the most common code smells devs run into, and more importantly, how to refactor them into something cleaner, safer, and easier to work with.

Let’s get into it.

There are two kinds of security tools: Ones that look great in audits, and ones that help developers write safer code.

Most static analysis tools fall into the first category. They scan your codebase, spit out a PDF, and move on. But if you're the one reviewing PRs, fixing bugs, or owning releases, you need something more useful than a checklist generator.

This guide isn’t here to repeat what you’ll find on a feature page. We reviewed 15+ SAST vendors in the US and focused on what matters in practice:

Do they catch useful issues?
Are the alerts fixable or just noise?
Can devs trust and use the tool in their flow?

Whether you're a solo dev looking for something lightweight, or part of an engineering org trying to build a real DevSecOps pipeline, this breakdown is for you.

And yes, we’ve included ourselves in the list. But the goal isn’t to pitch. It’s to help you choose a tool you won’t uninstall in 3 weeks.

Let’s get into it.

What Is a Code Smell? (Let’s Be Real)

Okay, quick reality check.

Most devs don’t spot a code smell by reading a blog post.

They spot it when something feels off.

Maybe it’s a method that scrolls longer than your salary slip. Maybe it's a function called processEverything() that’s somehow connected to literally everything.

Or maybe you open a file and immediately mutter:

“Who wrote this?”

Then git blame says: “You. Last April.”

Code smells are like the weird noises your car makes.
It still runs. You can technically ignore it.
But deep down, you know you're one line away from the engine falling out.

So, what exactly is a code smell?

It’s not a bug. It won’t break your build.

But it’s a signal that something in your code isn’t quite right. It might be too complex, too repetitive, or just weirdly structured. It works, but it's fragile. Hard to read, harder to change, and guaranteed to confuse the next person who touches it.

Usually, that person is you, in three months.

These smells tend to show up when you're:

Rushing to ship a feature
Copy-pasting from StackOverflow
"Temporarily" skipping cleanup because of deadlines (we see you 👀)

But here’s the thing: over time, these little smells pile up.

And what started as “just a little mess” turns into full-blown technical debt, the kind that blocks features, breaks tests, and ruins weekends.

So yeah, code smells are a warning, not a crash.

But the best devs don’t wait for the crash.
They learn to smell it early… and clean it up before it spreads.

And that’s where we’re headed next.

Let’s break down the 11 most common code smells, and more importantly, how to refactor each one without losing your sanity.

1. Long Method

Let’s be honest, long methods don’t start long.

You’re just building a quick feature. You add some logic. Then a few checks. Then a fetch call. A log here, a side effect there. And suddenly you’ve got a 100-line monster.

And the worst part? It still works. So nobody touches it.

Until they have to.

A long method is basically your brain trying to juggle five things at once: validation, transformation, API calls, conditionals, maybe even UI changes, all mixed into one place.

At some point, you lose the plot. You can't skim and know what it does. You have to read it like a novel. Slowly. Carefully. Nervously.

Why it’s a problem:

You can’t test it easily, too many things are going on.
You can’t debug it safely; one change breaks five things.
You can’t reuse parts because everything is tangled.

And if you’ve ever tried to change one small thing and ended up breaking three others? Yup. Classic long method symptoms.

What to do instead

Split it up by responsibility, not by line count.

If one chunk is validating inputs? That’s one small function.
Is it another chunk formatting or cleaning data? That’s another.
If one part is talking to an API? Great, give that its own name.

Think of your code like short paragraphs, each with a clear idea.

It’s not about making the method shorter. It’s about making the logic clearer. The next time you or a teammate reads it, they shouldn’t need coffee and 10 minutes of silence.

Rule of thumb?

If you can’t explain what the method does in one sentence, it’s doing too much.

Real-world example

Let’s say you're building a function to register a user:

Right now, it looks like this:

function registerUser(user) {
  if (!user.email.includes('@')) {
    throw new Error('Invalid email');
  }

  const cleanedData = {
    name: user.name.trim(),
    email: user.email.toLowerCase(),
    age: Number(user.age),
  };

  fetch('/api/register', {
    method: 'POST',
    body: JSON.stringify(cleanedData),
  }).then(() => {
    console.log('User registered!');
  });
}

Looks fine, right?

But even here, you’ve got three different jobs happening:

Validating the email
Cleaning and preparing data
Making the network call

Split it like this:

function registerUser(user) {
  validateEmail(user.email);
  const cleanedData = cleanUserData(user);
  sendUserToServer(cleanedData);
}

Now, each part is simple, readable, and has one clear job.

And if something breaks? You know exactly where to look.

2. Large Class

Have you ever open a class and scroll for what feels like a full minute?

You find methods for everything: database logic, UI updates, business rules, maybe even some leftover utils. It’s trying to handle login, sign-up, error handling, logging, and state management. All in one place.

That’s a Large Class. Or what some devs call a “God Object.”
Because it thinks it’s responsible for the entire world.

Why does it happen:

You keep adding logic to the same class “just for now.”
There’s no clear separation between concerns (e.g., logic vs display)
You’re scared to move stuff out because... something might break

And hey, if you’re in a rush, it’s easy to dump things in one file. But over time, large classes become brittle. They’re hard to test, harder to reuse, and terrifying to refactor.

What to do instead:

Split based on intent. Ask:

Is this class doing more than one type of job?
Can I group related behavior together and move it out?
Would this part make sense as its own class/module?

Let’s say you have a UserManager class that handles:

Validating input
Talking to a server
Formatting user data
Saving to local storage

You could split that into:

UserValidator
UserService (for API calls)
UserStorageHandler

That way, each class does one thing well, and you can test/fix them independently.

Rule of thumb?
If you find yourself saying, “Well this method is only used sometimes when X happens,” you probably need a new class.

3. Duplicate Code

This one’s easy to spot… and somehow still everywhere.

You copy a function. Change a line. Paste it somewhere else. Tell yourself:

“I’ll clean it later.”

Then 2 weeks go by.
Someone finds a bug. Fixes it… in one copy.
The other copy? Still broken.

Why it’s a problem:

Wastes time, fix in one place, forget the rest
Causes bugs, inconsistent changes across copies
Makes testing hard you’re testing the same thing twice

You’d be shocked how many bugs come down to:

“Oh... we had another version of this in utils-2.js.”

What to do instead:

If you’ve written the same logic twice (even if it’s not exactly the same), ask:

Can I extract this into a shared function?
Can I make the differences into parameters?

Even better: give it a clear name. Abstracting logic is good, but naming it well is what really makes it useful.

Let’s say you’re formatting user data in two different components:

const user = {
  name: name.trim().toUpperCase(),
  email: email.toLowerCase(),
};

Don’t copy-paste that logic, move it to:

function formatUser({ name, email }) {
  return {
    name: name.trim().toUpperCase(),
    email: email.toLowerCase(),
  };
}

Now it’s clean, reusable, and lives in one place.
You fix it once, and it’s fixed everywhere.

Rule of thumb?

If you find yourself using “cmd + c” in your code editor, pause and ask why.

4. Data Clumps

Sometimes you see the same three or four variables traveling together through half the codebase.

function sendEmail(name, email, subject, body) { ... }
function logEmail(name, email, subject, body) { ... }
function saveEmail(name, email, subject, body) { ... }

They’re like a little gang that never breaks up.
Where you find one, you find all four.

That’s a data clump, a sign that these values probably belong together. If you're constantly passing them as a group, it’s time to give them a home.

Why it’s a problem:

Repetition → more chances for mistakes
Long, messy function signatures
Confusing when you add/remove one, do you fix all calls?

It’s like carrying groceries one item at a time instead of using a bag.

What to do instead:

Create a data structure, even a simple object to represent the idea behind the group.

const emailInfo = {
  name: 'Alice',
  email: 'alice@example.com',
  subject: 'Hello',
  body: 'Just checking in.',
};

Now your functions get cleaner and clearer:

function sendEmail(emailInfo) { ... }
function logEmail(emailInfo) { ... }
function saveEmail(emailInfo) { ... }

And if the data structure changes? You fix it in one place.

Rule of thumb?

If the same 2–3 variables always appear together, group them. That’s your real object trying to be born.

5. Feature Envy

This one’s subtle, and sneaky.

You write a method inside Class A… but it spends most of its time accessing data from Class B.

Like:

class InvoicePrinter {
  print(invoice) {
    const total = invoice.getSubtotal() + invoice.getTax();
    const name = invoice.getCustomerName();
    const date = invoice.getDate();

    return `${name} - ${date}: ₹${total}`;
  }
}

If your method is constantly poking around someone else’s object , calling all its getters, using its fields , it’s envious. It wants to live in that other class.

Why it’s a problem:

Breaks encapsulation
Creates tight coupling
Makes maintenance harder , changes to Invoice can break InvoicePrinter

What to do instead:

Move the logic closer to the data.

Here, if the formatting logic is really about the invoice, then let the Invoice class own it.

class Invoice {
  formattedSummary() {
    const total = this.getSubtotal() + this.getTax();
    return `${this.getCustomerName()} - ${this.getDate()}: ₹${total}`;
  }
}

Now, other classes can simply call the invoice.formattedSummary(), no poking around in its internals.

Rule of thumb? If a method seems more interested in another object’s data than its own… maybe it’s living in the wrong house.

6. Switch Statements

We get it. You need different behavior based on a value. And switch looks clean… at first.

switch (user.role) {
  case 'admin':
    return showAdminDashboard();
  case 'editor':
    return showEditorDashboard();
  case 'guest':
    return showGuestDashboard();
  default:
    throw new Error('Unknown role');
}

Seems fine, right? But fast forward six months,
More roles. More logic. Now the switch is 50 lines long and appears in 3 different files.

This isn’t just messy, it’s a maintainability trap.

Why it’s a problem:

Violates Othe pen/Closed principle, you have to modify it every time something changes
Harder to test each case separately
Duplicated switch logic across the codebase

What to do instead:

Use polymorphism or simple lookup objects.

If you're in an object-oriented language, move the logic into the role classes themselves.

But in JavaScript or Python? A clean map works wonders:

const dashboards = {
  admin: showAdminDashboard,
  editor: showEditorDashboard,
  guest: showGuestDashboard,
};

function getDashboard(role) {
  const show = dashboards[role];
  if (!show) throw new Error('Unknown role');
  return show();
}

It’s cleaner, easier to extend, and avoids that huge switch/case block entirely.

Rule of thumb?

If your switch keeps growing, it’s a sign your logic wants to be spread out, not stacked up.

7. Shotgun Surgery

This one hits hard when you’ve worked on a big codebase.

You want to change one thing, say, how dates are formatted. But to make that change, you have to edit six files. Maybe:

A utils file
A component
A report class
A backend endpoint
A helper test stub
Oh, and a random config file no one remembers touching

That’s Shotgun Surgery, when a single change requires lots of little edits scattered across the codebase.

Why it’s a problem:

Slows you down massively
Makes code brittle, one missed change leads to bugs
Wastes mental energy trying to track everything
Breaks confidence, you’re scared to touch things

This usually happens when related logic is spread out, instead of being grouped or abstracted properly.

Real example:

Say you change how user birthdays are formatted across the app.

If you're formatting dates in:

The UserCard component
The ProfileModal
The PDFGenerator
And a CLI tool for exports

...and each of those does it slightly differently, you now have to hunt and fix each instance manually.

What to do instead:

Centralize related logic.
In this case, create a formatDate() utility, even if it’s just one line, and use it everywhere.

// utils/date.js
export function formatDate(date) {
  return new Intl.DateTimeFormat('en-IN').format(new Date(date));
}

Now, if formatting rules change (like locale or display), you update one function, not six.

Rule of thumb?

If changing one idea means opening multiple files, that idea needs a home.

8. Divergent Change

This is the evil twin of Shotgun Surgery.

Here, you’re editing the same file again and again, but for totally different reasons.

Imagine a UserProfile.js file that:

Renders the profile UI
Sends user updates to the server
Validates profile inputs
Applies business rules for age, name, etc.
Triggers analytics events when the user logs in

Any time the backend API changes? You touch this file.

Need to tweak UI layout? Same file.
Fix a validation bug? Same file.

Now this one file becomes a hotspot, touched by every kind of change. It’s trying to do too much.

Why it’s a problem:

High risk of introducing bugs
Merge conflicts galore (especially in teams)
Code coupling, unrelated changes affect each other
Slows you down, every change feels heavier

What to do instead:

Split by responsibility, not by UI layer or endpoint.

In the example above:

Move API logic to a service layer → userService.updateProfile()
Move validation to a separate module → validateProfile(data)
Keep UI concerns in the UI file

Now, when you tweak server logic or validation rules, you’re not messing with your component; you’re editing just what needs to change.

Rule of thumb?

If you edit the same file for unrelated reasons often, it’s doing too much.

9. Speculative Generality

This one is too common, especially in teams that over-architect early.

It’s when you write code for a future that may never come.

You define abstract classes, config files, plugin systems, inheritance layers, all “just in case” you need them later.

But no one ever does.

Real-world signs:

Empty interfaces like IUserHandler
Classes with one method that just calls another
Flags in the config that are never used
A factory system with one product

It’s like installing a 12-socket power strip when you only need to charge your phone.

Why it’s a problem:

Adds complexity without benefit
Confuses future devs, “Why is this even here?”
Slows down real development, you’re navigating abstractions you don’t need
Harder to refactor later, because it’s unclear what’s actually in use

What to do instead:

Build for today, not a fantasy future.

Keep your code simple until you actually need generalization.

Instead of:

class EmailSender {
  send(email) {
    // might support SMS later
  }
}

Just write:

function sendEmail(email) {
  // send it
}

If you eventually need SMS or push notifications? Cool, then refactor into a NotificationSender interface or strategy pattern.

Rule of thumb?

If the code says “this might be useful later” but isn’t useful now, cut it.

10. Inappropriate Intimacy

This is when two classes are way too close.
They’re constantly poking around in each other’s private parts.

You’ll see code like:

const userDetails = user._profile._meta.getInternalCode();

Or worse, one class does half its job by accessing fields or methods from another class that it shouldn’t even know exists.

It’s like one roommate constantly going into the other’s room, using their stuff, and rearranging the furniture. Sure, it works... until it breaks.

Why it’s a problem:

Creates tight coupling, changing one class breaks another
Violates encapsulation, you’re exposing internals
Makes code hard to reuse or refactor
Over time, creates tangled, fragile systems

Real-world example:

Let’s say you have a ReportGenerator class that needs data from User.

Instead of asking User for what it needs, the generator starts digging through internal properties.

class ReportGenerator {
  generate(user) {
    const name = user._details._personalInfo.name;
    const dob = user._details._personalInfo.dob;
    return `${name} - ${dob}`;
  }
}

Looks minor now, but what if User changes its internal structure?
Boom, every report breaks.

What to do instead:

Let each class define what it exposes through clear methods:

class User {
  getNameAndDob() {
    return {
      name: this.details.personalInfo.name,
      dob: this.details.personalInfo.dob,
    };
  }
}

Now your ReportGenerator becomes:

const { name, dob } = user.getNameAndDob();

Clean, clear, and no need to know how User stores stuff internally.

Rule of thumb?

If Class A knows too much about Class B’s internal state, that’s intimacy you don’t want.

11. Comments Instead of Clean Code

Ah, yes, the classic “This function sorts the list”, right above a method called sortList().

Or worse, a comment trying to explain a complex, unreadable function instead of... rewriting it.

// this reverses the array, skips the first element, then merges with another reversed array
function doThings(a, b) { ... }

That’s not helpful. That’s a band-aid on a broken leg.

Why it’s a problem:

Comments get outdated fast, code evolves, and comments don’t
Comments mask bad code instead of fixing it
Code should be as self-explanatory as possible

This doesn’t mean “never write comments.” It means:
If you need a comment to explain what a function does, maybe rewrite the function so it explains itself.

What to do instead:

Use good naming and small, focused functions.

Compare this:

calculate the final price with tax and discount
function fn(p, d, t) {
  return p - d + t;
}

To this:

function calculateFinalPrice(price, discount, tax) {
  return price - discount + tax;
}

Same logic. Zero comments. 10x more understandable.

Rule of thumb?

Good code needs fewer comments. If you’re writing a lot of comments, try writing better code instead.

So, what now?

If you’ve made it this far, you’ve got a solid grip on:

What code smells are
Why they matter
How to spot and fix the most common ones
And how to write code that doesn’t just work, but lasts

But honestly? You don’t have to do it all alone.

Why We’re Sharing CodeAnt (And Why It Matters)

Let’s be honest, fixing code smells sounds great on a blog.

But in a real sprint? With deadlines, reviews, and constant context-switching?

You usually ship first, clean later… and then never get to it.

And that’s exactly how technical debt builds up, slowly, silently, one messy function at a time. Not because you’re a bad dev. But the tools around you don’t nudge you toward better code at the moment.

That’s why we’re sharing CodeAnt.ai not as a product plug, but as a way to actually do the stuff we just talked about.

If you're working on a growing codebase, managing reviews, or just tired of firefighting the same bugs… CodeAnt can help you refactor smarter, detect smells early, and keep technical debt from ballooning out of control.

How CodeAnt.ai Solves This for Modern Dev Teams

Here’s what CodeAnt actually does, in plain dev-speak:

Catches Code Smells Instantly
While you’re writing code, CodeAnt can highlight smells like long methods, duplicate code, and complex logic, right in your IDE (VS Code + JetBrains supported).
One-Click Refactoring
You can literally right-click a function → hit “Refactor” → and let CodeAnt automatically clean up code smells, apply type hints, and fix anti-patterns.
AI That Understands Context
It doesn’t just scan files, it reads your intent, PR history, and project structure to make context-aware suggestions that won’t break your flow.
Pull Request Reviews Done Right
Every PR gets an AI-powered summary, quality review, security checks, and suggestions, so you’re not reviewing 200 lines manually.
End-to-End Code Health Dashboard
On the team level, you get visibility into what’s breaking, what’s improving, and what smells are recurring, with real reports.
Security + Compliance Built In
From SAST to secret detection to compliance checks, CodeAnt adds security reviews alongside code quality, no extra tools needed.

How AI Is Changing Code Refactoring (For Good)

The old way:

You push to GitHub
Run CI/CD
Linter complains
You fix it manually (or ignore it)

The new way, with AI:

The second you write messy or risky code, your AI tool nudges you
Not just with a warning, but with a fix
You click → it refactors
You move on

This is where tools like CodeAnt.ai, SonarQube, and ESLint are headed, but CodeAnt combines all of them with the intelligence of AI and the precision of static analysis, baked right into your dev workflow. And yes, that is why we raised $2 million to help cut the review and increase dev productivity.

Conclusion

If you’ve made it to the end, you already know:

Code smells don’t start out as big problems. They sneak in through rushed deadlines, unclear ownership, and the classic “I’ll clean it up later.”

But over time, they add up, creating technical debt that slows you down, bloats your codebase, and turns every simple change into a risk.

The truth? Most teams don’t ignore clean code because they don’t care.
They ignore it because the tools haven’t kept up with the pace of modern development.

You’re shipping faster. Your codebase is growing. Your team is scaling.

So your tools need to help you write clean code, not just punish you when you don’t.

That’s exactly why we built CodeAnt.ai.

It’s not just a code smell detector. It’s a complete AI-powered platform that:

Catches smells before they spread
Refactors your code with one click
Automates PR reviews and security checks
And gives you visibility into your code health, across your entire team

You don’t need to fight tech debt manually anymore.
You just need better tools.

✅ Want to see how CodeAnt can work for your team, in real time?
Book a free call with the founder to walk through your use case and explore how AI can help you write cleaner, safer code, faster.

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355 Bryant St. San Francisco, CA 94107, USA

11 Common Code Smells and How to Fix Them in 2025 [LATEST]

11 Common Code Smells and How to Fix Them in 2025 [LATEST]

Content

What Is a Code Smell? (Let’s Be Real)

So, what exactly is a code smell?

1. Long Method

Why it’s a problem:

What to do instead

Real-world example

2. Large Class

Why does it happen:

What to do instead:

3. Duplicate Code

Why it’s a problem:

What to do instead:

4. Data Clumps

Why it’s a problem:

What to do instead:

5. Feature Envy

Why it’s a problem:

What to do instead:

6. Switch Statements

Why it’s a problem:

What to do instead:

7. Shotgun Surgery

Why it’s a problem:

Real example:

What to do instead:

8. Divergent Change

Why it’s a problem:

What to do instead:

9. Speculative Generality

Real-world signs:

Why it’s a problem:

What to do instead:

10. Inappropriate Intimacy

Why it’s a problem:

Real-world example:

What to do instead:

11. Comments Instead of Clean Code

Why it’s a problem:

What to do instead:

So, what now?

Why We’re Sharing CodeAnt (And Why It Matters)

How CodeAnt.ai Solves This for Modern Dev Teams

How AI Is Changing Code Refactoring (For Good)

Conclusion

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