You’ve just spent hours solving a complex problem. Your code runs perfectly, passes all the test cases, and you’re feeling pretty good about yourself. Then, during code review, a senior developer tells you, “This works, but it’s not good enough.” Ouch.

If you’ve ever been in this situation, you’re not alone. Many developers, especially those early in their careers, face this seemingly contradictory feedback. How can something work correctly but still not be “good enough”?

In this article, we’ll explore the gap between functional code and professional-quality code, and why senior developers might push back on solutions that technically work but don’t meet higher standards.

Understanding the Gap Between “Working” and “Good” Code

First, let’s clarify something important: making code that works is a significant achievement, especially when you’re learning. But in professional environments, working code is just the minimum requirement.

Consider this analogy: imagine you need to write an essay. A passing essay communicates your points without major grammatical errors. But an excellent essay also has elegant structure, compelling language, thoughtful transitions, and shows deep understanding of the subject matter.

Similarly, code can exist on a spectrum from “barely works” to “exemplary”:

When a senior developer says your code isn’t good enough, they’re usually referring to a gap between these levels.

7 Common Reasons Your Working Code Gets Criticized

1. Performance Inefficiencies

One of the most common reasons working code gets rejected is poor performance. Your solution might work for the test cases, but what happens when it needs to process millions of records?

Consider this JavaScript function that finds duplicate numbers in an array:

// Beginner approach - O(n²) time complexity
function findDuplicates(array) {
    const duplicates = [];
    
    for (let i = 0; i < array.length; i++) {
        for (let j = i + 1; j < array.length; j++) {
            if (array[i] === array[j] && !duplicates.includes(array[i])) {
                duplicates.push(array[i]);
            }
        }
    }
    
    return duplicates;
}

This works, but a senior developer might point out:

A more efficient solution might use a hash map:

// More efficient approach - O(n) time complexity
function findDuplicates(array) {
    const seen = {};
    const duplicates = [];
    
    for (const num of array) {
        if (seen[num]) {
            if (seen[num] === 1) {
                duplicates.push(num);
            }
            seen[num]++;
        } else {
            seen[num] = 1;
        }
    }
    
    return duplicates;
}

This achieves the same result with O(n) time complexity, making it much more scalable.

2. Poor Readability and Maintainability

Code is read much more often than it’s written. Your teammates (and future you) will need to understand what your code does without excessive mental effort.

Consider this Python function:

def p(d, k):
    r = []
    for i in d:
        if i["a"] > k:
            r.append(i["n"])
    return r

It works, but what does it do? Compare with:

def get_products_above_price(products, price_threshold):
    expensive_products = []
    for product in products:
        if product["price"] > price_threshold:
            expensive_products.append(product["name"])
    return expensive_products

The second version communicates its purpose clearly through:

Senior developers value code that documents itself through clear naming and structure.

3. Lack of Error Handling

Beginners often write code that works perfectly… until something unexpected happens. Professional code anticipates potential issues and handles them gracefully.

Consider this function that divides two numbers:

function divide(a, b) {
    return a / b;
}

This works until someone passes zero as the second parameter, causing a division by zero error. A more robust version might be:

function divide(a, b) {
    if (typeof a !== 'number' || typeof b !== 'number') {
        throw new TypeError('Both arguments must be numbers');
    }
    
    if (b === 0) {
        throw new Error('Cannot divide by zero');
    }
    
    return a / b;
}

Good error handling includes:

4. Ignoring Established Patterns and Conventions

Every language and framework has established patterns and conventions. These aren’t just arbitrary rules; they make code more predictable for other developers.

For example, in React, a component that doesn’t follow conventions might look like:

function userProfile(p) {
    const [n, setN] = React.useState(p.name);
    const [a, setA] = React.useState(p.age);
    
    function c() {
        console.log(n, a);
    }
    
    return (
        <div>
            <h2>{n}</h2>
            <p>Age: {a}</p>
            <button onClick={c}>Log Info</button>
        </div>
    );
}

Following React conventions, it should be:

function UserProfile({ name, age }) {
    const [userName, setUserName] = React.useState(name);
    const [userAge, setUserAge] = React.useState(age);
    
    const handleLogInfo = () => {
        console.log(userName, userAge);
    };
    
    return (
        <div className="user-profile">
            <h2>{userName}</h2>
            <p>Age: {userAge}</p>
            <button onClick={handleLogInfo}>Log Info</button>
        </div>
    );
}

The improved version follows React conventions with:

5. Redundant or Duplicated Code

The DRY principle (Don’t Repeat Yourself) is fundamental to good code. Duplicated logic makes code harder to maintain because changes need to be made in multiple places.

Consider this Java code for a shopping cart:

public class ShoppingCart {
    public double calculateSubtotal(List<Item> items) {
        double subtotal = 0;
        for (Item item : items) {
            subtotal += item.getPrice() * item.getQuantity();
        }
        return subtotal;
    }
    
    public double calculateTax(List<Item> items) {
        double subtotal = 0;
        for (Item item : items) {
            subtotal += item.getPrice() * item.getQuantity();
        }
        return subtotal * 0.08;
    }
    
    public double calculateTotal(List<Item> items) {
        double subtotal = 0;
        for (Item item : items) {
            subtotal += item.getPrice() * item.getQuantity();
        }
        double tax = subtotal * 0.08;
        return subtotal + tax;
    }
}

Notice how the same calculation appears three times? A better approach would be:

public class ShoppingCart {
    public double calculateSubtotal(List<Item> items) {
        double subtotal = 0;
        for (Item item : items) {
            subtotal += item.getPrice() * item.getQuantity();
        }
        return subtotal;
    }
    
    public double calculateTax(List<Item> items) {
        return calculateSubtotal(items) * 0.08;
    }
    
    public double calculateTotal(List<Item> items) {
        double subtotal = calculateSubtotal(items);
        double tax = calculateTax(items);
        return subtotal + tax;
    }
}

The improved version calculates the subtotal once and reuses that functionality, making the code more maintainable.

6. Overengineering or Premature Optimization

Interestingly, sometimes code isn’t “good enough” because it’s trying too hard to be clever. Senior developers value simplicity and clarity over unnecessarily complex solutions.

Consider this overly complex function to check if a number is even:

function isEven(num) {
    return !Boolean(
        Array.from(
            { length: Math.abs(num) + 1 },
            (_, i) => i
        ).reduce((acc) => !acc)
    );
}

Versus the straightforward approach:

function isEven(num) {
    return num % 2 === 0;
}

Remember Donald Knuth’s famous quote: “Premature optimization is the root of all evil.” Sometimes the simplest solution is the best one.

7. Failing to Consider the Broader System

Code doesn’t exist in isolation. It’s part of a larger system with specific requirements, constraints, and patterns. Senior developers consider how code fits into the bigger picture.

For example, in a system that emphasizes immutability, this function would be problematic:

function addItemToCart(cart, item) {
    cart.items.push(item);
    cart.itemCount += 1;
    cart.total += item.price;
    return cart;
}

It directly mutates the cart object. A more system-appropriate approach might be:

function addItemToCart(cart, item) {
    return {
        ...cart,
        items: [...cart.items, item],
        itemCount: cart.itemCount + 1,
        total: cart.total + item.price
    };
}

This creates a new cart object with the updated values, respecting immutability principles.

Beyond Functionality: What Senior Developers Are Really Looking For

Code That’s Built to Last

Professional software isn’t a one-time solution; it’s a living entity that will be maintained, extended, and refactored over time. Senior developers evaluate code based on how well it accommodates future changes.

Questions they might ask include:

This forward-thinking perspective often leads to principles like SOLID:

These principles guide the creation of flexible, maintainable code structures.

Code That Respects Resources

Professional applications need to be mindful of resource usage, including:

Consider this Node.js function that reads a large file:

function processLargeFile(filePath) {
    // This loads the entire file into memory
    const content = fs.readFileSync(filePath, 'utf8');
    
    const lines = content.split('\n');
    
    for (const line of lines) {
        // Process each line
    }
}

For very large files, this could cause memory issues. A more resource-conscious approach would be:

function processLargeFile(filePath) {
    // This streams the file line by line without loading it all at once
    const fileStream = fs.createReadStream(filePath, { encoding: 'utf8' });
    const rl = readline.createInterface({
        input: fileStream,
        crlfDelay: Infinity
    });
    
    rl.on('line', (line) => {
        // Process each line
    });
    
    return new Promise((resolve) => {
        rl.on('close', resolve);
    });
}

This streaming approach uses minimal memory regardless of file size.

Code That Communicates Intent

Great code tells a story. It clearly communicates what it’s doing and why. Senior developers value code that reveals its purpose through structure, naming, and organization.

Consider these two SQL queries that do the same thing:

-- Query 1
SELECT c.id, c.name, COUNT(o.id)
FROM customers c
LEFT JOIN orders o ON c.id = o.customer_id
WHERE c.status = 'active'
GROUP BY c.id, c.name
HAVING COUNT(o.id) > 5
ORDER BY COUNT(o.id) DESC;

Versus:

-- Query 2
SELECT 
    c.id AS customer_id,
    c.name AS customer_name,
    COUNT(o.id) AS order_count
FROM 
    customers c
LEFT JOIN 
    orders o ON c.id = o.customer_id
WHERE 
    c.status = 'active'  -- Only include active customers
GROUP BY 
    c.id, c.name
HAVING 
    COUNT(o.id) > 5  -- Customers with more than 5 orders
ORDER BY 
    order_count DESC;  -- Most frequent customers first

The second query uses:

How to Bridge the Gap: From Working Code to Great Code

If you’re receiving feedback that your code works but isn’t good enough, here are practical steps to level up:

1. Study Design Patterns and Principles

Familiarize yourself with established software design patterns and principles. Resources like:

These resources provide frameworks for thinking about code structure and organization.

2. Read High-Quality Code

One of the best ways to improve is to study excellent code. Look at:

Pay attention to how they structure projects, handle errors, name variables, and organize functionality.

3. Embrace Code Reviews

Rather than seeing code reviews as criticism, view them as personalized learning opportunities. When receiving feedback:

The most growth happens when you understand the reasoning behind the feedback, not just the changes themselves.

4. Practice Refactoring

Take working code and practice improving it without changing its behavior. Tools like:

Can provide opportunities to practice refactoring skills.

5. Focus on One Aspect at a Time

Trying to improve everything at once can be overwhelming. Instead, focus on one aspect of code quality at a time:

This focused approach makes improvement more manageable and helps build lasting habits.

Case Study: Transforming “Working” Code Into “Good” Code

Let’s look at a complete example of transforming working code into high-quality code. We’ll start with a function that analyzes a list of products and returns various statistics.

Original Working Version

function analyze(p) {
    let t = 0;
    let max = p[0].price;
    let min = p[0].price;
    let c = 0;
    
    for (let i = 0; i < p.length; i++) {
        t = t + p[i].price;
        
        if (p[i].price > max) {
            max = p[i].price;
        }
        
        if (p[i].price < min) {
            min = p[i].price;
        }
        
        if (p[i].category === 'electronics') {
            c = c + 1;
        }
    }
    
    let a = t / p.length;
    
    return {
        t: t,
        a: a,
        max: max,
        min: min,
        c: c
    };
}

This code works, but it has several issues:

Improved Version

/**
 * Analyzes product data to extract price statistics and category counts.
 * 
 * @param {Array} products - Array of product objects with price and category properties
 * @param {string} categoryToCount - Category name to count occurrences of
 * @returns {Object} Statistics including total, average, min/max prices, and category count
 * @throws {Error} If products array is empty or invalid
 */
function analyzeProducts(products, categoryToCount = 'electronics') {
    // Validate input
    if (!Array.isArray(products) || products.length === 0) {
        throw new Error('Products must be a non-empty array');
    }
    
    // Ensure all products have a price property
    if (!products.every(product => typeof product.price === 'number')) {
        throw new Error('All products must have a numeric price property');
    }
    
    // Use reduce to calculate all statistics in a single pass
    const statistics = products.reduce((stats, product) => {
        // Update running total
        stats.totalPrice += product.price;
        
        // Update max and min prices
        stats.maxPrice = Math.max(stats.maxPrice, product.price);
        stats.minPrice = Math.min(stats.minPrice, product.price);
        
        // Count products in the specified category
        if (product.category === categoryToCount) {
            stats.categoryCount++;
        }
        
        return stats;
    }, {
        totalPrice: 0,
        maxPrice: products[0].price,
        minPrice: products[0].price,
        categoryCount: 0
    });
    
    // Calculate average price
    statistics.averagePrice = statistics.totalPrice / products.length;
    
    return {
        totalPrice: statistics.totalPrice,
        averagePrice: statistics.averagePrice,
        maxPrice: statistics.maxPrice,
        minPrice: statistics.minPrice,
        categoryCount: statistics.categoryCount,
        categoryName: categoryToCount
    };
}

The improved version addresses all the issues with:

This transformation illustrates how “working” code can be elevated to “good” code without changing the core functionality.

Understanding the Feedback Beneath the Criticism

When a senior developer says your code isn’t good enough, they’re usually trying to help you grow. Behind this feedback are often these implicit messages:

The most productive response is to ask questions like:

These questions transform criticism into a collaborative learning opportunity.

Conclusion: The Journey from Working Code to Great Code

The gap between code that works and code that excels is where professional growth happens. Every senior developer once wrote code that merely worked, and through feedback, study, and practice, they learned to write code that stands the test of time.

Remember that:

As you continue your coding journey, embrace the challenge of not just making things work, but making them work beautifully. The effort you invest in bridging this gap will pay dividends throughout your career, as you create solutions that are not just functional, but truly excellent.

Your working code isn’t “not good enough” in an absolute sense; it’s just the beginning of your journey toward mastery. Keep building, keep learning, and keep refining your craft.