ADH
Design Patterns
RefactoringAdvanced

Iterative Refactoring with AI

Systematically improve code quality through AI-guided refactoring cycles that maintain functionality while enhancing structure.

refactoringcode-qualitytechnical-debtmaintenance

Overview

Iterative Refactoring with AI combines AI analysis capabilities with systematic refactoring practices to safely improve code quality. AI identifies code smells, suggests improvements, and helps verify that refactoring preserves behavior, enabling continuous codebase improvement.

Problem

Refactoring legacy code is risky and often postponed: - Fear of breaking existing functionality - Difficulty understanding unfamiliar code - Lack of tests makes changes dangerous - Hard to prioritize what to refactor first

Solution

Use AI to guide and accelerate the refactoring process: - Analyze code for improvement opportunities - Suggest specific refactoring steps - Generate tests before refactoring - Verify behavior preservation after changes - Document the reasoning behind changes This creates a safety net that makes refactoring less risky and more systematic.

Implementation

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Code Examples

Before Refactoring
// Complex function with multiple responsibilities
function processOrder(order: any) {
  // Validate
  if (!order.items || order.items.length === 0) {
    throw new Error('No items');
  }
  if (!order.customer) {
    throw new Error('No customer');
  }

  // Calculate totals
  let subtotal = 0;
  for (let i = 0; i < order.items.length; i++) {
    subtotal += order.items[i].price * order.items[i].qty;
  }
  const tax = subtotal * 0.08;
  const total = subtotal + tax;

  // Save to database
  db.orders.insert({ ...order, subtotal, tax, total });

  // Send email
  sendEmail(order.customer.email, 'Order confirmed', `Total: $${total}`);

  return { subtotal, tax, total };
}

Original code mixes validation, calculation, persistence, and notification.

After AI-Guided Refactoring
// Separated concerns with clear responsibilities
function validateOrder(order: Order): ValidationResult {
  const errors: string[] = [];
  if (!order.items?.length) errors.push('No items');
  if (!order.customer) errors.push('No customer');
  return { valid: errors.length === 0, errors };
}

function calculateOrderTotals(items: OrderItem[]): OrderTotals {
  const subtotal = items.reduce(
    (sum, item) => sum + item.price * item.quantity, 0
  );
  const tax = subtotal * TAX_RATE;
  return { subtotal, tax, total: subtotal + tax };
}

async function processOrder(order: Order): Promise<ProcessedOrder> {
  const validation = validateOrder(order);
  if (!validation.valid) {
    throw new OrderValidationError(validation.errors);
  }

  const totals = calculateOrderTotals(order.items);
  const savedOrder = await orderRepository.save({ ...order, ...totals });
  await notificationService.sendOrderConfirmation(savedOrder);

  return savedOrder;
}

Refactored code separates concerns, uses dependency injection, and is more testable.

Best Practices

  • Never refactor without tests in place
  • Make small, incremental changes
  • Commit after each successful refactoring step
  • Use AI to explain unfamiliar code before changing it
  • Track technical debt reduction metrics

Considerations

Benefits
  • • Safer refactoring with AI-generated tests
  • • Systematic approach to technical debt reduction
  • • Better understanding of legacy code
  • • Documented reasoning for changes
  • • Incremental improvement with lower risk
Challenges
  • • AI may suggest over-engineering
  • • Time investment for thorough refactoring
  • • Risk of introducing new bugs despite tests
  • • Requires team buy-in for refactoring time
  • • AI may not understand domain-specific constraints

Related Patterns

Test Generation WorkflowAi Assisted Code Review