Code Refactoring Tool
Restructure code for better design and maintainability with AI-powered refactoring that applies SOLID principles, design patterns, and clean code practices. Automatically extracts methods from large functions, eliminates code duplication, improves naming clarity, and reduces coupling. Handles Extract Method, Extract Class, Rename Variable, Simplify Conditionals, and Replace Magic Numbers across Python, JavaScript, Java, C++, and 100+ languages without changing behavior.
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Issue Description
Hint: Paste your code and click Refactor to restructure it for better design, maintainability, and clean architecture.
How It Works
- Step 1: Paste your code that needs refactoring—large functions with multiple responsibilities, duplicated logic across methods, or tightly coupled components.
- Step 2: The AI analyzes code structure to identify refactoring opportunities including long methods (>20 lines), high cyclomatic complexity, code smells like feature envy, and violations of SOLID principles.
- Step 3: Advanced refactoring algorithms apply transformations such as Extract Method to break down large functions, Extract Class for separation of concerns, Introduce Parameter Object to reduce parameter lists, and Replace Conditional with Polymorphism for complex if-else chains.
- Step 4: Receive refactored code with detailed explanations of applied patterns, improved maintainability metrics, and assurance that external behavior remains unchanged through semantic equivalence preservation.
Before vs After: Refactoring Impact
| Feature | Original Code | Refactored Code |
|---|---|---|
| Code Structure | Monolithic functions | Modular, single-responsibility |
| Duplication | Repeated logic | DRY principle applied |
| Naming | Unclear variable names | Self-documenting code |
| Coupling | Tight dependencies | Loose coupling, high cohesion |
| Design Patterns | Ad-hoc solutions | Standard patterns applied |
Code Refactoring Examples
Example 1: Extract Method Refactoring
function processOrder(order) {
// Validate order
if (!order.items || order.items.length === 0) {
throw new Error('Order must have items');
}
if (!order.customer || !order.customer.email) {
throw new Error('Customer email required');
}
// Calculate total
let total = 0;
for (let item of order.items) {
total += item.price * item.quantity;
if (item.discount) {
total -= item.price * item.quantity * item.discount;
}
}
// Apply shipping
if (total < 50) {
total += 10;
}
// Send email
const subject = 'Order Confirmation';
const body = `Thank you for your order. Total: $${total}`;
sendEmail(order.customer.email, subject, body);
return { orderId: generateId(), total, status: 'confirmed' };
}function processOrder(order) {
validateOrder(order);
const total = calculateOrderTotal(order);
sendOrderConfirmation(order.customer, total);
return {
orderId: generateId(),
total,
status: 'confirmed'
};
}
function validateOrder(order) {
if (!order.items || order.items.length === 0) {
throw new Error('Order must have items');
}
if (!order.customer || !order.customer.email) {
throw new Error('Customer email required');
}
}
function calculateOrderTotal(order) {
let total = calculateItemsSubtotal(order.items);
total = applyShippingCost(total);
return total;
}
function calculateItemsSubtotal(items) {
return items.reduce((sum, item) => {
const itemTotal = item.price * item.quantity;
const discount = item.discount ? itemTotal * item.discount : 0;
return sum + itemTotal - discount;
}, 0);
}
function applyShippingCost(subtotal) {
const FREE_SHIPPING_THRESHOLD = 50;
const SHIPPING_COST = 10;
return subtotal < FREE_SHIPPING_THRESHOLD
? subtotal + SHIPPING_COST
: subtotal;
}
function sendOrderConfirmation(customer, total) {
const subject = 'Order Confirmation';
const body = `Thank you for your order. Total: $${total}`;
sendEmail(customer.email, subject, body);
}Key Changes:
The refactoring applies Extract Method pattern to break down a 25-line monolithic function into six focused functions, each with a single responsibility following the Single Responsibility Principle. The original function mixed validation, calculation, and notification logic, making it hard to test and maintain. The refactored version separates concerns—validateOrder handles input validation, calculateOrderTotal manages pricing logic, and sendOrderConfirmation deals with notifications. Magic numbers (50, 10) are replaced with named constants (FREE_SHIPPING_THRESHOLD, SHIPPING_COST) improving readability. The calculateItemsSubtotal uses Array.reduce for functional programming style, eliminating manual loop management. Each extracted function can now be unit tested independently, improving test coverage. The main processOrder function reads like documentation, clearly showing the order processing workflow. This refactoring reduces cyclomatic complexity from 5 to 2 per function, making code easier to understand and modify. The pattern is applicable to any large function mixing multiple concerns.
Example 2: Replace Conditional with Polymorphism
def calculate_shipping(order_type, weight, distance):
if order_type == 'standard':
base_cost = 5.00
cost = base_cost + (weight * 0.5) + (distance * 0.1)
elif order_type == 'express':
base_cost = 15.00
cost = base_cost + (weight * 0.8) + (distance * 0.2)
elif order_type == 'overnight':
base_cost = 30.00
cost = base_cost + (weight * 1.0) + (distance * 0.3)
elif order_type == 'international':
base_cost = 50.00
cost = base_cost + (weight * 2.0) + (distance * 0.5)
else:
raise ValueError(f'Unknown order type: {order_type}')
return costfrom abc import ABC, abstractmethod
class ShippingStrategy(ABC):
def __init__(self, base_cost, weight_rate, distance_rate):
self.base_cost = base_cost
self.weight_rate = weight_rate
self.distance_rate = distance_rate
@abstractmethod
def calculate(self, weight, distance):
return (self.base_cost +
(weight * self.weight_rate) +
(distance * self.distance_rate))
class StandardShipping(ShippingStrategy):
def __init__(self):
super().__init__(base_cost=5.00, weight_rate=0.5, distance_rate=0.1)
def calculate(self, weight, distance):
return super().calculate(weight, distance)
class ExpressShipping(ShippingStrategy):
def __init__(self):
super().__init__(base_cost=15.00, weight_rate=0.8, distance_rate=0.2)
def calculate(self, weight, distance):
return super().calculate(weight, distance)
class OvernightShipping(ShippingStrategy):
def __init__(self):
super().__init__(base_cost=30.00, weight_rate=1.0, distance_rate=0.3)
def calculate(self, weight, distance):
return super().calculate(weight, distance)
class InternationalShipping(ShippingStrategy):
def __init__(self):
super().__init__(base_cost=50.00, weight_rate=2.0, distance_rate=0.5)
def calculate(self, weight, distance):
return super().calculate(weight, distance)
class ShippingCalculator:
_strategies = {
'standard': StandardShipping,
'express': ExpressShipping,
'overnight': OvernightShipping,
'international': InternationalShipping
}
@classmethod
def calculate_shipping(cls, order_type, weight, distance):
strategy_class = cls._strategies.get(order_type)
if not strategy_class:
raise ValueError(f'Unknown order type: {order_type}')
strategy = strategy_class()
return strategy.calculate(weight, distance)
# Usage
cost = ShippingCalculator.calculate_shipping('express', 10, 100)Key Changes:
This refactoring applies the Strategy design pattern to eliminate a complex if-elif chain, following the Open/Closed Principle—open for extension, closed for modification. The original function requires modification every time a new shipping type is added, violating OCP. The refactored version uses polymorphism through abstract base class ShippingStrategy, allowing new shipping types to be added without changing existing code. Each shipping type is now a separate class with encapsulated calculation logic, improving testability—each strategy can be tested independently. The ShippingCalculator uses a dictionary to map order types to strategy classes, providing O(1) lookup versus O(n) for if-elif chains. The abstract base class enforces the calculate method contract through @abstractmethod decorator, ensuring all strategies implement the required interface. This pattern eliminates code duplication—the calculation formula is defined once in the base class. Adding a new shipping type now requires creating a new class and registering it in the _strategies dictionary, without touching existing code. This refactoring increases initial code volume but dramatically improves maintainability, extensibility, and adherence to SOLID principles. The pattern is essential for any system with type-based conditional logic that may grow over time.
Frequently Asked Questions
What is code refactoring?
Code refactoring is the process of restructuring existing code without changing its external behavior. It improves code design, readability, maintainability, and quality by applying better patterns, simplifying complex logic, reducing duplication, and following clean code principles like SOLID and DRY.
How does AI code refactoring work?
Our AI analyzes your code structure, identifies refactoring opportunities like complex functions, duplicated code, poor naming, and tight coupling. It then restructures the code by extracting methods, applying design patterns, improving separation of concerns, simplifying logic, and enhancing code organization while preserving functionality.
What types of refactoring does it perform?
The tool performs multiple refactoring types: Extract Method (breaking down large functions), Extract Class (improving separation), Rename Variables/Functions (better clarity), Simplify Conditionals (reducing complexity), Remove Duplication (DRY principle), Apply Design Patterns (Strategy, Factory, etc.), Improve Error Handling, and Optimize Data Structures.
Is the code refactoring tool free?
Yes! Every new user gets 5 free lifetime credits. After that, purchase credits starting at $10 for 100 credits. Credits never expire and there are no subscriptions.
Which programming languages are supported?
We support 100+ programming languages including Python, JavaScript, TypeScript, Java, C++, C#, PHP, Ruby, Go, Rust, Swift, Kotlin, and more. The refactoring applies language-specific patterns, idioms, and best practices.
Will refactoring change my code's behavior?
No! Proper refactoring preserves your code's external behavior and functionality. The tool only changes the internal structure, design, and organization. However, always test refactored code thoroughly to ensure it works correctly in your specific environment and with your dependencies.