Code Refactoring Best Practices

Have you even worked on a team of software developers and the code is absolutely horrible. We are talking spaghetti code and inefficient code like nested loops, which is a big no-no according to Big-O.

As we write software applications, it is important to tackle the problem of writing messy code so that it is easy to understand. I’m talking about code that is so bad that it gives you a headache trying to figure it out.

Why bother with refactoring? Software, much like a building, needs maintenance to remain functional and efficient. Over time, additions and modifications can lead to a codebase that’s difficult to read and expensive to change. Refactoring addresses these issues by improving the nonfunctional attributes of the software. This, in turn, leads to enhanced code quality and easier maintenance down the line.

In the following sections, I’ll share with you an example of spaghetti code and a toolkit for code refactoring best practices. These techniques will not only make your code more elegant, but they’ll also foster an environment where future changes can be implemented with greater ease and less risk of introducing bugs.

Spaghetti Code Example

I’m a fan of Italian food, but when it comes to coding, Italian food and spaghetti just don’t blend well together! 😄

Refactoring isn’t a task you do in isolation; it’s a vital part of the software development process that intertwines with development cycles. I’ll present real-world case studies where refactoring propelled projects forward, yielding significant gains in efficiency and reducing technical debt.

“Spaghetti code” refers to a programming style characterized by a tangled, unstructured, and difficult-to-follow codebase. It typically arises from haphazard development practices, a lack of planning, or frequent modifications without proper refactoring. Here’s an example of spaghetti code in Python:

def calculate_total_price(items):
    total_price = 0

    # Loop through each item in the list
    for item in items:
        # Check if the item is in stock
        if item['quantity'] > 0:
            # Calculate the item price
            if item['type'] == 'book':
                if item['genre'] == 'fiction':
                    price = item['price'] * 0.9
                elif item['genre'] == 'non-fiction':
                    price = item['price'] * 0.8
                else:
                    price = item['price']
            elif item['type'] == 'electronic':
                if item['brand'] == 'Apple':
                    price = item['price'] * 1.2
                elif item['brand'] == 'Samsung':
                    price = item['price'] * 1.1
                else:
                    price = item['price']
            else:
                price = item['price']

            # Update total price
            total_price += price * item['quantity']

    # Apply discount if total price is above $1000
    if total_price > 1000:
        total_price *= 0.9

    return total_price

In this example:

• The code lacks clear structure and readability.
• The logic for calculating item prices is convoluted and nested, making it hard to understand and maintain.
• There are redundant conditions and calculations.
• The function’s purpose (calculating the total price of items) is buried within a maze of if statements and loops.

To improve this code, you could refactor it by breaking it into smaller, more manageable functions, simplifying conditional logic, and adding comments to explain the purpose of each section.

To refactor the spaghetti code into a more organized and readable structure, we can break down the logic into smaller, focused functions, simplify conditional checks, and improve code clarity. Here’s a refactored version:

def calculate_item_price(item):
    price = item['price']
    if item['type'] == 'book':
        price = apply_book_discount(price, item['genre'])
    elif item['type'] == 'electronic':
        price = apply_electronic_markup(price, item['brand'])
    return price

def apply_book_discount(price, genre):
    if genre == 'fiction':
        return price * 0.9
    elif genre == 'non-fiction':
        return price * 0.8
    return price

def apply_electronic_markup(price, brand):
    if brand == 'Apple':
        return price * 1.2
    elif brand == 'Samsung':
        return price * 1.1
    return price

def calculate_total_price(items):
    total_price = 0
    for item in items:
        if item['quantity'] > 0:
            total_price += calculate_item_price(item) * item['quantity']
    return total_price

def apply_discount(total_price):
    if total_price > 1000:
        return total_price * 0.9
    return total_price

items = [
    {'type': 'book', 'genre': 'fiction', 'price': 10, 'quantity': 2},
    {'type': 'book', 'genre': 'non-fiction', 'price': 15, 'quantity': 1},
    {'type': 'electronic', 'brand': 'Apple', 'price': 100, 'quantity': 1},
    {'type': 'electronic', 'brand': 'Samsung', 'price': 200, 'quantity': 1}
]

total_price = calculate_total_price(items)
final_price = apply_discount(total_price)
print("Total Price after discount:", final_price)

In this refactored version:

• Each function has a clear and single responsibility.
• Complex conditional logic is moved into separate functions for better readability.
• The main calculation logic is contained within the calculate_total_price function, which iterates over the items and calculates the total price.
• The apply_discount function applies a discount if the total price exceeds a certain threshold.
• By breaking down the code into smaller functions with clear names and responsibilities, we make it easier to understand, maintain, and extend.

The Golden Rules of Refactoring

Refactoring isn’t just about changing code. Adopting a methodology is essential to keeping the process manageable and the code integrity intact.

The principle of starting small is paramount. Tackle one problem at a time to avoid overwhelming the system or the developers. This approach minimizes risk and makes the changes easier to test and debug. Consider it the divide-and-conquer strategy of coding.

There’s a simple guideline that resonates with every seasoned developer: the Boy Scout Rule. It encourages you to leave the code better than you found it, making small enhancements with each opportunity. Consistent application of this rule can result in significant collective improvement over time.

Refactoring should always aim for clarity and simplicity. A common misconception is that complex code is somehow better or more sophisticated. In reality, the beauty of code lies in its readability and the ease with which others can understand and maintain it.

Finally, rigorous testing safeguards the integrity of code during the refactoring process. Implementing a robust testing framework ensures that any changes made don’t introduce new bugs and that the software continues to function as expected.

With these foundational rules in place, let’s consider how to approach the inevitable challenges of refactoring. Refactoring can seem daunting, especially when dealing with a large and complex codebase or balancing the need for new features.

Overcoming Common Refactoring Challenges

Embarking on a refactoring initiative isn’t without its hurdles. One daunting prospect is facing legacy code. Often large and without sufficient tests, this code can be a minefield for developers. The key here is not to overhaul everything overnight. Instead, I recommend identifying the most critical parts of the system that could benefit from refactoring and focusing on those areas first. It’s crucial to write tests for these segments before altering the code to ensure you’re not introducing new issues.

Another tug-of-war situation is balancing refactoring efforts with the pressure to roll out new features. It’s common for stakeholders to prioritize new developments over behind-the-scenes quality improvements. I’ve found that communicating the long-term benefits of refactoring, such as reduced maintenance costs and faster future development, can help align their expectations with the technical needs.

Clear communication with your team is just as essential. During refactoring, it’s easy for team members to step on each other’s toes. Transparency is vital. Use version control tools to manage changes efficiently and make sure everyone is aware of what’s being refactored. Regular meetings to discuss progress and challenges can maintain clarity and cohesion within the team.

Understanding that refactoring is not an end in itself but part of an ongoing process of improvement sets the stage for the next section. We’ll delve into real-world examples that underscore how best practices in refactoring are applied and bring tangible benefits to projects. More importantly, we’ll look at how you can measure the success of your refactoring efforts and ensure they contribute to a culture of continuous improvement.

Conclusion

Consistency is key, and I cannot stress enough the importance of making refactoring a habitual part of your workflow. Teams that thrive are the ones that merge refactoring with their daily development activities, ensuring CLEAN, MAINTAINABLE, and SCALABLE code is the standard, not the exception.

Read my other article about best practices.

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