What is code refactoring? 

Code refactoring is the process of restructuring existing computer code without changing its external behavior. The goal is to improve the nonfunctional attributes of the software. Think of it as cleaning up your workspace: while it doesn’t directly contribute to the completion of your tasks, it makes the process smoother, more efficient, and more enjoyable.

Code refactoring can be as simple as renaming a variable to make its purpose clearer or as complex as breaking down a monolithic system into a series of microservices. The goal is to improve the readability, efficiency, and maintainability of the code without interfering with its primary functions.

We’ll discuss the main principles of refactoring, show techniques and examples, and show how generative AI can be a game changer for teams faced with challenging refactoring projects.

Key principles of refactoring 

Refactoring is not just about making changes to the code; it’s about making the right changes. There are several principles that guide this process, ensuring that our refactoring efforts are effective and beneficial.

1. Do no harm

The first and foremost principle of code refactoring is to “do no harm.” That means whatever changes we make to the code, the software’s functionality should remain consistent. We’re not adding new features or fixing bugs; we’re improving the code’s structure and design.

A developer working on refactoring should always ensure that their modifications don’t break the software or introduce new bugs. The software should behave the same way before and after the refactoring process.

2. Refactor in small steps

Another key principle of refactoring is to make small, incremental changes. It’s tempting to overhaul the entire codebase in one fell swoop, but that’s often a recipe for disaster. Instead, we should make one small change at a time, test it, and then move on to the next.

This approach reduces the risk of introducing new bugs and makes it easier to identify the cause if something goes wrong.

3. Maintain a robust suite of tests

A robust suite of tests is a critical tool for refactoring. Automated tests give us the confidence to make changes to the code, knowing that if we inadvertently break something, the tests will catch it. These tests serve as a safety net — they provide instant feedback, alerting us if our modifications have inadvertently changed the software’s behavior.

4. Refactor code on an ongoing basis

The final principle is to integrate refactoring into the regular development lifecycle. Refactoring should not be a one-off task, done only when the code becomes unmanageable. Instead, it should be a regular part of the development workflow, akin to tidying up our workspace at the end of each day.

This continuous refactoring approach helps prevent technical debt from accumulating and keeps the codebase clean and manageable.

Benefits of code refactoring 

While refactoring involves effort, time, and sometimes, a fair bit of courage, the benefits it brings are substantial.

Improved code readability and maintainability

One of the significant benefits of refactoring is improved code readability. A clean, well-structured codebase is easier to read, understand, and maintain. It’s like a well-organized library: finding the book (or code snippet) you need is quick and straightforward.

This improved readability benefits not just the original developer but everyone who works on the project. It makes onboarding new team members easier, facilitates code reviews, and makes the code more self-explanatory, reducing the need for external documentation.

Better performance

Refactoring can also enhance software performance. By optimizing the code, we can make the software run faster, consume less memory, and respond more quickly to user inputs. This performance boost can lead to a better user experience, making the software more pleasant and satisfying to use.

Reduced technical debt

Technical debt is the cost of postponing good development practices. Just like financial debt, it accumulates interest: the longer we leave it, the harder it becomes to pay off. Refactoring helps us reduce this technical debt, keeping our codebase clean and manageable.

Easier debugging

A well-refactored codebase makes bug identification and resolution easier. When the code is clean and well-structured, it’s easier to spot anomalies and inconsistencies. Moreover, when each function or module is small and focused, it’s easier to isolate the problem and fix it. 

Code refactoring techniques 

Here are some of the common techniques used by developers to refactor code:

Extract method

The extract method is a refactoring technique that involves breaking down a complex method into smaller, more manageable pieces. This technique is particularly useful when a method is performing multiple tasks, making it hard to understand. The extract method can improve the readability and maintainability of the code, making the refactoring process more straightforward and efficient.

Red/green/refactor

The red/green/refactor technique is a fundamental part of test-driven development (TDD). It involves writing a failing test (red), making it pass by writing code (green), and then refactoring the code to improve its design (refactor). This technique can help ensure that your refactoring efforts do not negatively impact the functionality of the code.

Abstraction

Abstraction is a powerful technique that can greatly simplify the refactoring process. It involves hiding the details of complex code and providing a simplified interface. Abstraction can make the code easier to understand and maintain, reducing the complexity and making the refactoring process less daunting.

Composing methods

“Composing methods” refers to the practice of breaking down a method or function into a series of smaller methods, each of which performs a single task. This technique can help improve the readability and maintainability of the code, making it easier to refactor. Composing methods can also help identify and remove duplicate code, which can further streamline the refactoring process.

Simplifying methods

“Simplifying methods” refers to the practice of simplifying complex methods or functions to make them easier to understand and maintain. This can involve removing unnecessary code, simplifying complicated expressions, and replacing complex conditional logic with simpler constructs.

Preparatory refactoring

Preparatory refactoring is a technique that involves making small, incremental changes to the code to prepare it for larger changes. This can involve simplifying complex methods, removing duplicate code, or improving the design of the code. Preparatory refactoring can help make the larger refactoring task less daunting and more manageable.

Learn more in our detailed guide to code refactoring techniques (coming soon).

Code refactoring examples in popular programming languages 

Now let’s look at some practical examples of refactoring in commonly used programming languages:

Code refactoring in Java

Example 1: Renaming variables

The code below is functional, but it’s not user-friendly for other developers who may need to maintain or enhance the code later:

int a = 5;
int b = 10;
int c = a + b;

This code can be refactored by renaming the variables to make the code more readable and understandable:

int numberOne = 5;
int numberTwo = 10;
int sumOfNumbers = numberOne + numberTwo;

Learn more in our detailed guide to code refactoring in Java (coming soon).

Example 2: Extracting methods

Another common refactoring technique in Java is method extraction. This is particularly useful when you have a long method that’s doing too many things:

public void printDetails() {
    System.out.println("Name: " + name);
    System.out.println("Age: " + age);
    System.out.println("Address: " + address);
}

We can refactor the above code by extracting methods:

public void printDetails() {
    printName();
    printAge();
    printAddress();
}


private void printName() {
    System.out.println("Name: " + name);
}


private void printAge() {
    System.out.println("Age: " + age);
}


private void printAddress() {
    System.out.println("Address: " + address);
}

Code refactoring in Python

Example 1: Simplifying nested if statements

Python’s readability makes it easy to spot nested if statements that can be simplified: 

def check_marks(marks):
    if marks >= 60:
        if marks >= 75:
            return "Distinction"
        else:
            return "First Class"
    else:
        return "Fail"

This code can be refactored to reduce complexity and increase readability:

def check_marks(marks):
    if marks >= 75:
        return "Distinction"
    elif marks >= 60:
        return "First Class"
    else:
        return "Fail"

Example 2: Replacing temp with query

In Python, you can refactor your code by replacing temporary variables with a query:

def calculate_total(price, quantity):
    total = price * quantity
    return total

The refactored code might look like this:

def calculate_total(price, quantity):
    return price * quantity

Code refactoring in C

Example 1: Replacing magic numbers with named constants

In C, you can improve code readability by replacing “magic numbers” (which might be unclear to other developers) with named constants.

float calculate_area(float radius) {
    return 3.14159 * radius * radius;
}

The refactored code might look like this:

#define PI 3.14159
float calculate_area(float radius) {
    return PI * radius * radius;
}

Example 2: Extracting code into functions

Extracting code into functions is one of the most common refactoring techniques in C. For example, consider this code:

void print_details() {
    printf("Name: %sn", name);
    printf("Age: %dn", age);
    printf("Address: %sn", address);
}

It can be refactored as follows:

void print_name() {
    printf("Name: %sn", name);
}
void print_age() {
    printf("Age: %dn", age);
}
void print_address() {
    printf("Address: %sn", address);
}
void print_details() {
    print_name();
    print_age();
    print_address();
}

Code refactoring in C#

Example 1: Removing dead code

Dead code is code that’s never executed. Here’s an example of dead code in C#:

public int CalculateTotal(int price, int quantity) {
    int total = price * quantity;
    int discount = 0; // This is dead code
    return total;
}

Here’s the refactored code:

public int CalculateTotal(int price, int quantity) {
    return price * quantity;
}

Example 2: Inlining temporary variables

In C#, you can refactor your code by inlining temporary variables:

public int CalculateTotal(int price, int quantity) {
    int total = price * quantity;
    return total;
}

Refactored code:

public int CalculateTotal(int price, int quantity) {
    return price * quantity;
}

Challenges of code refactoring 

Here are some of the key challenges you might face when refactoring code:

Inadequate test coverage

Inadequate test coverage leaves your code vulnerable to bugs and other issues. Without comprehensive tests, there’s no safety net to catch potential errors that may arise during the refactoring process. The absence of robust tests can make refactoring a precarious endeavor.

Large codebase or legacy system

Huge codebases or legacy systems often contain spaghetti code, making them difficult to understand and even harder to refactor. If the codebase is large and complex, the risk of introducing bugs or breaking existing functionality is high, and the task can quickly become overwhelming.

Lack of documentation

A common challenge in code refactoring is the lack of adequate documentation. When the original intent, design decisions, and functionality of the code are not well-documented, understanding and modifying the code becomes significantly harder. This lack of documentation can lead to misinterpretation of the code’s purpose, increasing the risk of introducing errors during refactoring.

Difficulty in estimating time

Finally, estimating the time required for refactoring can be a significant challenge. The complexity of the codebase, the scope of the changes, and the level of test coverage are just some of the factors that can affect the time needed for refactoring.

Best practices for code refactoring 

Despite the challenges, these best practices can help you succeed in your code refactoring efforts:

Plan your refactoring project and timeline carefully

Refactoring requires a well-considered plan and timeline. You need to understand the scope of your refactoring project, set realistic goals, and allocate sufficient time and resources to achieve those goals.

The planning phase involves identifying parts of your codebase that need refactoring, establishing the order in which you’ll tackle them, and estimating the time each task will take. You also need to factor in potential setbacks and build some flexibility into your timeline.

Review dependencies

Before you begin refactoring your code, you need to understand the dependencies within your codebase. Dependencies can be a major source of complexity and can make your refactoring process more challenging. By mapping out your dependencies, you can discover opportunities to simplify your code by eliminating unnecessary dependencies or consolidating related ones.  

It’s even more important to update dependencies to the latest versions, apply security patches, and remove dependencies that are no longer maintained by their creators. This is critical for improving the security of legacy software but should be done with care to address breaking changes in new versions of the dependencies. 

Reuse the existing tech stack

To ensure efficient and effective refactoring, it’s crucial to reuse the existing tech stack as much as possible. This approach minimizes the learning curve for the development team and leverages existing knowledge and resources. 

By focusing on the existing technologies, teams can identify underutilized features or functions that could be better exploited, leading to a more streamlined and coherent codebase. This practice also helps maintain consistency across the project and reduces the risk of introducing new bugs or compatibility issues associated with new technologies.

Focus on progress, not perfection

It’s easy to get caught up in trying to make the code perfect, but this can lead to endless refactoring that doesn’t add value to your software.

Instead, aim for incremental improvements. Each small change you make contributes to the overall quality of your code, making it more readable, maintainable, and flexible. Remember: refactoring is a continuous process, and you can always make further improvements in the future.

Use refactoring tools

Refactoring can be a tedious and time-consuming process, but fortunately, there are tools available that can make your job easier. Refactoring tools automate some of the repetitive tasks involved in refactoring, reducing human error and speeding up the process.

These tools can help you identify parts of your code that need refactoring, suggest improvements, and even perform some refactoring tasks automatically. They can also provide insights into your code’s structure and dependencies, assisting you in making informed refactoring decisions.

Automating code refactoring with generative AI

Given the challenges of code refactoring, recent advances in generative AI can be a big help to development teams. Tabnine is an AI-powered coding assistant that can predict and generate code completions in real time and provide automated code refactoring suggestions, which are sensitive to the context of your software project.

Tabnine integrates with your integrated development environment (IDE). As you type in your IDE, Tabnine analyzes the code and comments, predicting the most likely next steps and offering them as suggestions for you to accept or reject.

Tabnine utilizes a large language model (LLM) trained on reputable open source code with permissive licenses, StackOverflow Q&A, and even your entire codebase (Enterprise feature). This means it generates more relevant, higher quality, and more secure code than other tools on the market. 

Tabnine is the AI assistant you can trust and that you control

Today, 70% of developers code with AI. When implementing AI in an organization, it’s crucial to consider various aspects. Tabnine stands out with the highest standards of privacy and security. Unlike other AI coding tools, Tabnine places special emphasis on code privacy, intellectual property protection, and open source compliance. With a dedicated mission to bring AI to every facet of software development, Tabnine ensures seamless integration while prioritizing the privacy and security of user code:

Code privacy

Tabnine’s AI models can be isolated, with no external connectivity and no data retention, ensuring that user code remains completely private and secure. 

IP protection

Tabnine never stores user code and exclusively trains its generative AI on open source code with permissive licenses, mitigating the risk of intellectual property litigation. 

Open source compliance

Tabnine ensures complete security by not training its AI models on code with nonpermissive licenses, providing full transparency regarding the code used for training. By contrast, Microsoft Copilot trains on nonpermissive open source licenses, including GPL licenses with copyleft clauses, potentially exposing companies to legal risks. Although a filter is available to remove problematic code from suggestions, it may not always be foolproof, leaving the legal risk unresolved.

Since launching our first AI coding assistant in 2018, Tabnine has pioneered generative AI for software development. Tabnine helps development teams of every size use AI to accelerate and simplify the software development process without sacrificing privacy and security. Tabnine boosts engineering velocity, code quality, and developer happiness by automating the coding workflow through AI tools customized to your team. With more than one million monthly users, Tabnine typically automates 30-50% of code creation for each developer and has generated more than 1% of the world’s code.

Get started with Tabnine Pro for free today, or contact us to learn how we can help your engineering team be happier and more productive.