The Power of Clean Code: Good Coding Practices Matter

Anyone can write code that only computer can understand. Good programmers write code that anyone can understand

Introduction – My Journey Towards Clean, Maintainable Code

When I first started programming in college, like many of my peers, I was deeply immersed in competitive programming. The excitement of solving problems quickly and ranking high on platforms like CodeChef and LeetCode kept me motivated. However, I soon realised that while competitive programming sharpened my problem-solving skills, it didn't always prepare me for the challenges I would face in real-world software development.

In competitive coding, the focus is on speed and efficiency—solving a problem in the shortest time with the most optimised solution. But in real-world development, it's not just about writing code that works; it's about writing clean, maintainable code that is scalable and understandable by others. The ability to adapt and evolve code as a project grows, without introducing errors or creating confusion for teammates, is critical for long-term success.

In this article, I’ll explain why good coding practices are essential for building sustainable software. While my industry experience is still less and growing, I’ve learned a lot from both my peers and a lot from seniors, and I’m eager to share the insights I’ve gained. I’ll also reflect on some of the mistakes I made early on in my journey and how I learned to prioritise clean, maintainable code—something that competitive programming didn't teach me.

Why Good Code Matters

Good code is the foundation of successful software development. It’s not just about making things work—it’s about creating code that is maintainable, scalable, and understandable. In real-world projects, where code can stretch into thousands of lines, poorly organised file structure and long, convoluted files can quickly become a nightmare. Finding the right line of code in a massive file can be frustrating and time-consuming.

This concept won’t take much time to explain because everyone knows it—but it’s often the very thing that gets ignored. We all know that clean, concise code is critical, yet we still fall into the trap of writing overly complex or disorganized code.

Good code makes it easier to:

• Collaborate: Well-organised, readable code helps teams work together efficiently.
• Debug: Clear code simplifies troubleshooting and reduces the time spent fixing bugs.
• Scale: Code that’s structured properly can grow with the project without becoming unmanageable.
• Future-proof: Clean, concise code is adaptable, allowing for easier updates, modifications, and additions.

In the long run, following good coding practices saves time, reduces errors, and makes your codebase more flexible for future changes—ultimately leading to better software quality.

My Mistakes and How I Learned the Importance of Good Code

If you'd prefer to skip this section, feel free to do so—I’ve shared my personal journey and some of the mistakes I made, many of which are common pitfalls. I'll dive into those mistakes and their solutions in more detail in the upcoming section.

In my journey as a full-stack developer at a fast-paced consumer facing startup, I’ve had to quickly adapt to new technologies and programming languages. The pressure to deliver ultra-high-paced solutions for production meant that I often jumped straight into coding solutions without paying enough attention to best practices. While I was eager to get things done, I quickly learned the hard way that bad code practices not only lead to frustration but also slow down the development process in the long run.

Fortunately, I had a senior mentor who provided invaluable feedback on my code early in my career. After one of my pull requests, I received over 100 comments highlighting mistakes in my code—many of which were related to basic coding practices. At first, I was overwhelmed, but looking back, I am grateful to have had such a great mentor. Not everyone gets that kind of feedback early on, but I quickly realised how crucial it is to listen and learn from those mistakes.

Here are a few key mistakes I made and the lessons I learned from them:

1. Ignoring/Not Knowing Naming Conventions: One of the first mistakes I made was not paying attention to the naming conventions of the language I was using. Whether it was the case of classes, objects, functions, variables, or constants, I often didn't follow the language-specific rules, leading to inconsistent code that was harder to maintain.
2. Poor File Structure and Code Organisation: At the start, I didn’t pay much attention to file structuring. Everything ended up in a few giant files, making it extremely difficult to navigate or add new features.
3. Neglecting Code Formatting and Consistency: In my rush to deliver solutions quickly, I neglected proper formatting. Things like indentation, spacing, and line breaks were inconsistent, leading to messy code that was hard to follow, even for me.
4. Mixing Logic and Functionality in Large Files: I used to write long functions and place most of the logic directly in the main code file. While this got the job done, it quickly became difficult to scale or modify.

I am incredibly grateful for what the feedback from my senior mentor taught me. Each of these mistakes helped me understand that good code is not just about solving problems; it’s about solving them in a way that is clean, maintainable, and scalable.

I quickly realised that investing time in writing clean code pays off in the long run. While high-paced environments often push you to code quickly, adopting good practices from the start will save you and your team time and frustration in the future.

Common Mistakes and Their Solutions

As I reflected on my own experiences and the feedback I received, I realised that many of the mistakes I made were quite common across the development community. The good news is that these issues can be easily avoided with a bit of mindfulness and the right practices. Below are few of the most common mistakes I’ve observed—and how to fix them (I will be using Flutter/Dart code examples):

1. Not Learning Naming Conventions of the Language

Mistake: Every programming language has its own naming conventions (e.g., camelCase, snake_case, PascalCase), and not following these conventions can make your code look inconsistent and hard to maintain.

Example (Incorrect Naming):

class userData {
  String userName;
  int user_age;

  userData(this.userName, this.userAge);

  String userInfo() {
    return '$userName, $user_age';  // Inconsistent method naming
  }
}        

Example (Correct Naming):

class UserData {
  String userName;
  int userAge;

  UserData(this.userName, this.userAge);

  String getUserInfo() {
    return '$userName, $userAge';  // Consistent camelCase naming
  }
}        

2. Not Confident in OOP Concepts

Mistake: Object-Oriented Programming (OOP) is a core concept in many modern languages. Not understanding or confidently applying OOP principles (like inheritance, polymorphism, encapsulation, and abstraction) leads to poorly structured code.

Example (Incorrect OOP Application):

// Procedural code, no classes
double calculateArea(double radius) {
  return 3.14 * radius * radius;
}

double calculateCircumference(double radius) {
  return 2 * 3.14 * radius;
}        

Example (Correct OOP Application):

class Circle {
  double radius;

  Circle(this.radius);

  double calculateArea() {
    return 3.14 * radius * radius;
  }

  double calculateCircumference() {
    return 2 * 3.14 * radius;
  }
}

void main() {
  var circle = Circle(5);
  print(circle.calculateArea());
}        

3. Poor File Structuring

Mistake: Keeping all the code in one file, especially when working on large projects, can lead to messy codebases that are hard to manage and navigate.

Why It’s a Problem: When files become too large, it becomes difficult to locate specific functionality, and maintaining or extending the code can become a nightmare.

Example (Poor Structuring):

// Everything in one file (hard to navigate and maintain)

Map<String, dynamic> getUserData() {
  return {'name': 'John Doe', 'age': 30};
}

double calculateDiscount(double price) {
  return price * 0.1;
}

void printReceipt() {
  var userData = getUserData();
  var price = 100.0;
  var discount = calculateDiscount(price);
  print("Receipt: ${userData['name']} - Discount: $discount");
}        

Example (Good Structuring):

/src
    /models
        user.dart
    /utils
        discount.dart
    /controllers
        receipt_controller.dart        

4. Using Incorrect or Inconsistent Data Types

Mistake: Using inconsistent data types for variables, especially when dealing with dates, can cause significant confusion. For instance, using a string to represent a date rather than the appropriate DateTime type leads to errors or unexpected behavior when performing date-related calculations.

Example (Incorrect Data Type Use):

// Incorrect: Using string to store date information
String startDate = "2024-11-01";  // String (should be DateTime)
String endDate = "2024-11-10";    // String (should be DateTime)        

Example (Correct Data Type Use):

 // Correct: Using DateTime to store date information   
DateTime startDate = DateTime(2024, 11, 1);   
DateTime endDate = DateTime(2024, 11, 10);        

5. Ignoring Design Patterns

Mistake: Not using or understanding design patterns—especially creational, structural, and behavioural patterns—can lead to poorly structured, hard-to-maintain code.

Why It’s a Problem: Without design patterns, your code will likely be more fragile, harder to scale, and prone to duplicated logic.

Solution: Learn and apply design patterns based on the type of problem you're solving. By learning and applying design patterns, developers can:

• Solve common problems in a standardised and efficient way.
• Ensure code is maintainable, scalable, and easy to extend.
• Avoid reinventing the wheel for commonly encountered software development challenges.

Below are some most used and important patterns to consider:

• Creational Patterns (Singleton, Factory, Abstract Factory)
• Structural Patterns (Adapter, Facade, Proxy)
• Behavioural Patterns (Observer, Strategy)

6. Mixing Business Logic and Functionality

Mistake: Mixing business logic with core technical functionality (such as database calls, API requests, or UI updates) is a common pitfall. When developers don’t separate these concerns, the code becomes more difficult to maintain, test, and extend. A common scenario is when business rules are intertwined with technical code within the same class or function, making the codebase fragile and unstructured.

Why It’s a Problem: When business logic and technical functionality are not separated, any change in one area (such as a business rule change or a database structure change) can require changes in many parts of the codebase, leading to bugs and broken functionality. This can also create tight coupling between different layers of your application, making it difficult to scale, test, or refactor your codebase in the future.

Solution: To avoid this, separate business logic from technical functionality by using appropriate architectural patterns. The MVVM (Model-View-ViewModel) pattern is a popular solution for this in Flutter. In backend applications, patterns like Service Layer or Clean Architecture help achieve the same goal. These patterns help create a clear separation between business logic (which can change frequently) and technical code (which deals with things like API calls or database access).

Example (Using MVVM in Flutter):

In Flutter, the MVVM pattern allows us to separate concerns into three main layers:

1. Model – Represents the data structure (like a User object).
2. View – Handles the UI layer (e.g., Widgets).
3. ViewModel – Holds the business logic and interacts with the Model to provide data to the View.

7. Under-confidence in Asking for Time to Write Good Code Under Pressure

Mistake: The pressure of tight deadlines can sometimes lead developers to rush through writing good code. This often results in quick fixes, ignoring best practices, and cutting corners, only to face long-term consequences.

Solution: Never underestimate the value of writing clean, maintainable code, even under time pressure. If needed, ask for extra time to refactor code and make it more robust. Communication is key—explain why quality matters for the long-term success of the project.

Conclusion: The Long-Term Value of Clean Code

In conclusion, the importance of clean, maintainable code cannot be overstated. While it's tempting to prioritise speed and get things working quickly—especially in fast-paced environments—it's crucial to understand that writing good code today saves you time, effort, and frustration tomorrow. Code that is easy to read, well-structured, and follows best practices makes it easier for your team to collaborate, debug issues, and scale projects effectively.

As I’ve shared throughout this article, I’ve made my fair share of mistakes. I’ve learned, sometimes the hard way, that investing in good coding practices early leads to more sustainable and efficient solutions in the long run. By following design patterns, adhering to naming conventions, separating concerns, and maintaining consistent code structure, you're setting yourself and your team up for long-term success.

It’s easy to get caught in the rush of delivering features quickly, but remember, clean code is an investment. It might seem like it takes extra time upfront, but it will save countless hours of debugging, refactoring, and rebuilding in the future.

So, whether you’re just starting out or you're already deep into your development journey, always prioritise writing clean, maintainable code. It will not only make your job easier but will also help you build more reliable, scalable software that stands the test of time.

Feel free to reflect on the practices and patterns discussed, and keep refining your approach to coding—because good code isn't just about making things work; it’s about making things work well, now and in the future.