Code readability is a cornerstone of efficient programming. We’ve all heard the adage that code is read more often than it’s written. Yet despite the proliferation of code formatting tools promising to make our code more readable, many developers still struggle with comprehension when reviewing code.

So why aren’t your code formatting tools delivering on their promise of improved readability? In this comprehensive guide, we’ll explore the limitations of automated formatting tools, what truly makes code readable, and how to move beyond superficial fixes to create genuinely maintainable code.

Table of Contents

Understanding Code Readability

Before diving into why formatting tools might be falling short, let’s establish what we mean by “readable code.” Code readability encompasses several dimensions:

Most formatting tools focus predominantly on visual clarity, which is only one piece of the readability puzzle. This narrow focus explains why even perfectly formatted code can still be difficult to understand.

Consider this perfectly formatted but difficult-to-understand example:

function processData(data) {
    const x = data.map(i => i.v);
    const y = x.filter(v => v > 0);
    const z = y.reduce((a, b) => a + b, 0);
    return z / y.length;
}

The formatting is consistent, but the variable names and structure don’t communicate the code’s purpose. Compare it to:

function calculateAverageOfPositiveValues(dataPoints) {
    const allValues = dataPoints.map(point => point.value);
    const positiveValues = allValues.filter(value => value > 0);
    const sumOfPositiveValues = positiveValues.reduce((sum, value) => sum + value, 0);
    
    return sumOfPositiveValues / positiveValues.length;
}

Same functionality, similar formatting, but vastly different readability.

The Limitations of Automated Formatting Tools

Popular code formatting tools like Prettier, ESLint, Black, or gofmt have transformed how teams maintain consistent code style. However, they have inherent limitations:

1. They Focus on Syntax, Not Semantics

Formatting tools can ensure your braces align and your indentation is consistent, but they can’t understand what your code is trying to accomplish. They can’t tell you that your variable name x should be userAccountBalance or that your function is doing too many things at once.

Consider this formatting-compliant code:

function f(a, b, c) {
    let x = 0;
    if (a) {
        x = b + c;
    } else {
        x = b - c;
    }
    return x;
}

A formatter will ensure the braces and indentation are consistent, but it won’t suggest renaming the function to calculateResult or the variables to more descriptive names.

2. They Can’t Assess Logical Structure

Code formatters don’t evaluate whether your code’s organizational structure makes sense. They won’t tell you when:

For example, a formatter will happily format a 500-line function with nested if statements 10 levels deep. It might look consistent, but it won’t be readable.

3. They Can Sometimes Make Readability Worse

In some cases, strict formatting rules can actually reduce readability by breaking up logical groupings or forcing unnatural line breaks. Consider this example of a complex SQL query being built:

// Before formatting
const query = 
    "SELECT users.name, users.email, " +
    "COUNT(orders.id) AS order_count, " +
    "SUM(orders.amount) AS total_spent " +
    "FROM users " +
    "LEFT JOIN orders ON users.id = orders.user_id " +
    "WHERE users.status = 'active' " +
    "GROUP BY users.id " +
    "HAVING total_spent > 1000 " +
    "ORDER BY total_spent DESC";

// After automated formatting
const query = "SELECT users.name, users.email, " + "COUNT(orders.id) AS order_count, " + "SUM(orders.amount) AS total_spent " + "FROM users " + "LEFT JOIN orders ON users.id = orders.user_id " + "WHERE users.status = 'active' " + "GROUP BY users.id " + "HAVING total_spent > 1000 " + "ORDER BY total_spent DESC";

The formatter has made the code technically “correct” but has eliminated the visual structure that made the SQL query components easy to identify.

4. They Don’t Account for Context

Formatting tools apply the same rules universally, without understanding the specific context of the code. Sometimes, deviating from standard formatting can actually enhance readability in specific situations.

For instance, some mathematical or tabular data might be more readable with specific alignment:

// Human-formatted for clarity
const matrix = [
    [1.0, 0.0, 0.0],
    [0.0, 1.0, 0.0],
    [0.0, 0.0, 1.0]
];

// After formatting tool
const matrix = [
    [1.0, 0.0, 0.0],
    [0.0, 1.0, 0.0],
    [0.0, 0.0, 1.0]
];

In this case, the formatting tool preserved the readability, but in more complex examples, the tool might rearrange the spacing in ways that make the matrix structure less visually apparent.

Beyond Formatting: What Actually Makes Code Readable

To truly improve code readability, we need to look beyond what automated formatters can provide. Here are the aspects of readability that require human judgment:

1. Meaningful Naming

Perhaps nothing impacts readability more than how we name things. Good names serve as documentation and make code self-explanatory:

// Poor naming
function calc(arr) {
    let res = 0;
    for (let i = 0; i < arr.length; i++) {
        res += arr[i].val;
    }
    return res;
}

// Better naming
function calculateTotalRevenue(transactions) {
    let totalRevenue = 0;
    for (let i = 0; i < transactions.length; i++) {
        totalRevenue += transactions[i].amount;
    }
    return totalRevenue;
}

No formatting tool can make these naming improvements for you. They require understanding the code’s purpose and context.

2. Appropriate Abstraction

Breaking complex operations into well-named functions with single responsibilities dramatically improves readability:

// Without appropriate abstraction
function processUserData(users) {
    // 100 lines of complex code mixing multiple concerns
}

// With appropriate abstraction
function processUserData(users) {
    const validUsers = filterActiveUsers(users);
    const enrichedUsers = addUserMetadata(validUsers);
    const sortedUsers = sortByPriority(enrichedUsers);
    
    return generateUserReports(sortedUsers);
}

function filterActiveUsers(users) {
    // 20 focused lines
}

function addUserMetadata(users) {
    // 25 focused lines
}

// And so on...

The second approach is far more readable because it separates concerns and creates a clear narrative of what the code is doing.

3. Consistent Patterns and Idioms

Using consistent patterns throughout your codebase reduces the cognitive load of understanding new code. When developers recognize familiar patterns, they can focus on the unique aspects of the code rather than figuring out basic structure:

// Consistent pattern for API request handlers
async function getUserHandler(req, res) {
    try {
        const user = await userService.getUser(req.params.id);
        return res.json({ success: true, data: user });
    } catch (error) {
        return handleApiError(error, res);
    }
}

async function createUserHandler(req, res) {
    try {
        const user = await userService.createUser(req.body);
        return res.json({ success: true, data: user });
    } catch (error) {
        return handleApiError(error, res);
    }
}

Once a developer understands this pattern, every new handler they encounter will be immediately familiar.

4. Strategic Comments

While code should be as self-explanatory as possible, strategic comments can significantly enhance readability by explaining “why” rather than “what”:

// Don't do this
// Increment i
i++;

// Do this
// We're using a custom increment to handle the special case of overflow
// when operating in legacy compatibility mode
i = customIncrement(i);

Comments are most valuable when they explain non-obvious design decisions, business rules, or complex algorithms.

The Cognitive Aspects of Code Comprehension

Understanding how humans process and comprehend code can help us write more readable software. Research in program comprehension highlights several key findings:

1. Chunking and Mental Models

Humans understand code by building mental models and “chunking” related information. When code is structured to support these natural cognitive processes, it becomes more readable.

For example, grouping related operations together:

// Hard to chunk mentally
const name = user.name;
const products = getProducts();
const email = user.email;
const filteredProducts = filterProductsByPreference(products, user.preferences);
const phone = user.phone;
const sortedProducts = sortProductsByRelevance(filteredProducts);

// Easier to chunk mentally
// User information
const name = user.name;
const email = user.email;
const phone = user.phone;

// Product processing
const products = getProducts();
const filteredProducts = filterProductsByPreference(products, user.preferences);
const sortedProducts = sortProductsByRelevance(filteredProducts);

The second example supports natural chunking by grouping related operations, making it easier to comprehend.

2. Progressive Disclosure

Code is most readable when it reveals details progressively, starting with high-level concepts and allowing the reader to dive deeper as needed. This is why well-structured code with appropriate abstraction is easier to understand:

function processPayment(order) {
    validateOrder(order);
    calculateTotals(order);
    chargeCustomer(order);
    sendReceipt(order);
}

// Readers can stop here for a high-level understanding,
// or continue to implementation details if needed
function validateOrder(order) {
    // Implementation details...
}

This structure allows readers to understand the high-level flow before diving into details.

3. Cognitive Load and Working Memory

Humans have limited working memory capacity. Code that requires tracking many variables, conditions, or nested levels simultaneously is inherently harder to understand.

Consider this hard-to-follow code:

function processData(data) {
    let result = [];
    for (let i = 0; i < data.length; i++) {
        if (data[i].type === 'A' || data[i].type === 'B') {
            if (data[i].value > 10 && (!data[i].isProcessed || data[i].priority === 'high')) {
                if (checkAvailability(data[i].id) && data[i].region !== 'excluded') {
                    result.push(transformItem(data[i]));
                }
            }
        }
    }
    return result;
}

Versus this more manageable version:

function processData(data) {
    return data
        .filter(isEligibleType)
        .filter(meetsValueThreshold)
        .filter(isAvailableInRegion)
        .map(transformItem);
}

function isEligibleType(item) {
    return item.type === 'A' || item.type === 'B';
}

function meetsValueThreshold(item) {
    return item.value > 10 && (!item.isProcessed || item.priority === 'high');
}

function isAvailableInRegion(item) {
    return checkAvailability(item.id) && item.region !== 'excluded';
}

The second example reduces cognitive load by breaking complex conditions into named functions and using a pipeline pattern that’s easier to follow.

Balancing Automation and Human Judgment

The key to truly readable code lies in finding the right balance between automated formatting tools and human judgment. Here’s how to strike that balance:

1. Use Formatters as a Foundation, Not a Complete Solution

Automated formatters provide a solid baseline for visual consistency. Use them to handle the mechanical aspects of formatting so your team can focus on higher-level readability concerns:

2. Supplement with Linting Rules for Semantic Checks

While basic formatters focus on whitespace and syntax, linters can enforce some semantic rules:

Tools like ESLint for JavaScript, Pylint for Python, or RuboCop for Ruby can help catch some semantic issues that basic formatters miss.

3. Establish Team Guidelines for What Tools Can’t Check

Create explicit team guidelines for aspects of readability that tools can’t verify:

These human-enforced guidelines are crucial for aspects of readability that require judgment and context.

4. Use Code Reviews to Enforce Readability

Code reviews provide the human judgment layer that automated tools lack. Train your team to evaluate code not just for correctness but for readability:

The best teams view readability feedback as valuable rather than nitpicking.

Practical Strategies for Truly Readable Code

Beyond understanding the limitations of formatting tools, here are practical strategies to create genuinely readable code:

1. Write Code for the Reader, Not the Computer

Computers will execute any syntactically correct code, regardless of how it’s structured. The true audience for your code is other developers (including your future self).

Before committing code, ask yourself: “If someone who’s never seen this project before reads this code, will they understand what it does and why?”

2. Tell a Story with Your Code

Well-written code reads like a story, with a clear beginning, middle, and end. Each function should have a single, clear purpose that’s evident from its name and structure.

async function processOrderCheckout(cart, user) {
    // Beginning: Validation and preparation
    validateCartItems(cart);
    const shippingAddress = getShippingAddress(user);
    
    // Middle: Core business logic
    const order = createOrderFromCart(cart, user);
    const paymentResult = await processPayment(order, user.paymentMethods);
    
    // End: Finalization and side effects
    if (paymentResult.success) {
        sendOrderConfirmation(order, user.email);
        updateInventory(cart.items);
        clearUserCart(user.id);
    }
    
    return { order, paymentResult };
}

This code tells a clear story of the checkout process from beginning to end.

3. Optimize for the Common Case

Structure your code to make the most common path through it the most readable. Edge cases and error handling are important, but they shouldn’t obscure the primary purpose of the code.

// Hard to follow the main flow
function processOrder(order) {
    if (!order) {
        throw new Error('Order is required');
    }
    
    if (!order.items || order.items.length === 0) {
        throw new Error('Order must have items');
    }
    
    if (!order.customerId) {
        throw new Error('Order must have a customer ID');
    }
    
    // The actual business logic is buried under validation
    const total = calculateTotal(order.items);
    applyDiscounts(order, total);
    chargeCustomer(order.customerId, total);
    // More business logic...
}

// Main flow is clear, validation is separated
function processOrder(order) {
    validateOrder(order);
    
    const total = calculateTotal(order.items);
    applyDiscounts(order, total);
    chargeCustomer(order.customerId, total);
    // More business logic...
}

function validateOrder(order) {
    if (!order) {
        throw new Error('Order is required');
    }
    
    if (!order.items || order.items.length === 0) {
        throw new Error('Order must have items');
    }
    
    if (!order.customerId) {
        throw new Error('Order must have a customer ID');
    }
}

The second example makes the main flow more apparent by separating validation concerns.

4. Use Consistent Patterns

Consistency is a powerful tool for readability. When patterns are consistent, developers can focus on what the code does rather than how it’s structured.

For example, if you’re working with React components, adopt a consistent structure:

// A consistent component pattern
function UserProfile({ user }) {
    // 1. Hooks
    const [isEditing, setIsEditing] = useState(false);
    
    // 2. Derived state
    const fullName = `${user.firstName} ${user.lastName}`;
    
    // 3. Event handlers
    function handleEditClick() {
        setIsEditing(true);
    }
    
    // 4. Render helpers
    function renderActionButtons() {
        return (
            <div className="actions">
                {isEditing ? (
                    <SaveButton onClick={handleSave} />
                ) : (
                    <EditButton onClick={handleEditClick} />
                )}
            </div>
        );
    }
    
    // 5. Main render
    return (
        <div className="user-profile">
            <h2>{fullName}</h2>
            <div className="user-details">
                {/* Details here */}
            </div>
            {renderActionButtons()}
        </div>
    );
}

When all components follow this pattern, developers immediately know where to look for specific aspects of the component.

5. Refactor for Readability

Readability isn’t just for new code. Regularly refactoring existing code to improve readability pays dividends in maintenance costs:

Even small improvements accumulate over time to create more maintainable codebases.

Team Approaches to Code Readability

Readability is a team effort. Here’s how to build a team culture that values and enforces readable code:

1. Create a Readability Guide

Develop a team-specific readability guide that goes beyond basic formatting rules. Include:

This guide should evolve with your team and codebase.

2. Conduct Readability-Focused Code Reviews

Train team members to evaluate code specifically for readability during reviews. Questions to consider:

3. Pair on Readability Improvements

Pair programming sessions specifically focused on improving readability can be highly effective:

This approach leverages the fact that explaining code to others is a powerful way to identify readability issues.

4. Measure and Reward Readability

Consider making readability a measurable and rewarded aspect of code quality:

What gets measured and rewarded gets done.

The Future of Code Readability Tools

While current formatting tools have limitations, the future looks promising for more advanced readability assistance:

1. AI-Assisted Semantic Analysis

Machine learning models like those powering GitHub Copilot are beginning to understand code semantics, not just syntax. Future tools might:

2. Cognitive Complexity Analysis

Beyond simple metrics like cyclomatic complexity, future tools might evaluate how difficult code is for humans to understand:

3. Context-Aware Formatting

Future formatters might be smart enough to adapt their rules based on context:

4. Interactive Readability Tools

Rather than just applying fixed rules, future tools might work interactively with developers:

Conclusion

Code formatting tools provide a valuable foundation for consistent code style, but they address only the surface-level aspects of readability. True readability requires human judgment, semantic understanding, and a focus on how humans comprehend code.

To create genuinely readable code:

  1. Use formatting tools for what they’re good at: enforcing consistent visual style
  2. Focus on meaningful naming, appropriate abstraction, and clear structure
  3. Consider the cognitive aspects of how humans understand code
  4. Build team practices that value and enforce readability
  5. Recognize that readability is an ongoing process, not a one-time fix

Remember that the goal of readable code isn’t just aesthetic satisfaction—it’s reduced bugs, faster onboarding, more efficient maintenance, and ultimately, a more productive and happier development team.

By moving beyond superficial formatting to focus on what truly makes code comprehensible to humans, you’ll create codebases that remain maintainable and extendable for years to come.

What readability practices have you found most effective in your team? How do you balance automated tools with human judgment? Share your experiences and continue the conversation about creating truly readable code.