Tutorials

Smart Debugging with AI - Project Bolt Platform

Master AI-powered debugging techniques in Project Bolt. Learn how to efficiently diagnose and fix code issues using intelligent debugging tools.

•Project Bolt Team

Smart Debugging with AI

Learn how to use Project Bolt's AI-powered debugging tools to quickly identify and fix issues in your code.

Introduction

AI-powered debugging offers:

  • Automated error detection
  • Root cause analysis
  • Fix suggestions
  • Performance optimization
  • Security vulnerability detection

Basic Debugging Features

Error Analysis

The AI can analyze error messages and stack traces:

try {
  // Some code that throws an error
} catch (error) {
  // AI: Analyze this error
  console.error('Error occurred:', error);
  // AI will provide detailed analysis and fix suggestions
}

Code Inspection

Automatically detect potential issues:

// AI: Inspect this React component for issues
function UserProfile({ user, updateUser }) {
  const [loading, setLoading] = useState(false);
  
  useEffect(() => {
    // AI will flag missing dependency
    fetchUserData();
  }, []);
  
  async function fetchUserData() {
    setLoading(true);
    try {
      const data = await api.getUser(user.id);
      updateUser(data);
    } catch (error) {
      console.error(error);
    } finally {
      setLoading(false);
    }
  }
  
  // Component render...
}

Advanced Debugging Tools

Memory Leak Detection

Identify and fix memory leaks:

// AI: Check for memory leaks
function DataViewer() {
  const [data, setData] = useState([]);
  const subscription = useRef(null);
  
  useEffect(() => {
    subscription.current = api.subscribe(newData => {
      setData(prev => [...prev, newData]);
    });
    
    // AI will suggest cleanup
    return () => {
      subscription.current?.unsubscribe();
    };
  }, []);
  
  return <DataList data={data} />;
}

Performance Profiling

Analyze and optimize performance:

// AI: Profile this function for performance
function processLargeDataset(data) {
  // AI will suggest optimizations
  return data
    .filter(item => item.isValid)
    .map(item => transformItem(item))
    .reduce((acc, item) => acc + item.value, 0);
}

// AI suggested optimization:
function processLargeDatasetOptimized(data) {
  let sum = 0;
  for (const item of data) {
    if (item.isValid) {
      sum += transformItem(item).value;
    }
  }
  return sum;
}

Debugging Techniques

1. Smart Logging

Use AI to add strategic log points:

// AI: Add smart logging
async function processOrder(order) {
  logger.info('Starting order processing', { orderId: order.id });
  
  try {
    await validateOrder(order);
    logger.debug('Order validated', { 
      orderId: order.id, 
      items: order.items.length 
    });
    
    const result = await processPayment(order);
    logger.info('Payment processed', { 
      orderId: order.id, 
      amount: order.total,
      transactionId: result.transactionId 
    });
    
    return result;
  } catch (error) {
    logger.error('Order processing failed', {
      orderId: order.id,
      error: error.message,
      stack: error.stack
    });
    throw error;
  }
}

2. Automated Testing

Generate tests for bug reproduction:

// AI: Generate test for this bug
describe('Order Processing Bug', () => {
  it('should handle partial refunds correctly', async () => {
    const order = mockOrder({
      total: 100,
      refundAmount: 30
    });
    
    const result = await processRefund(order);
    
    expect(result.remainingBalance).toBe(70);
    expect(result.refundStatus).toBe('partial');
    expect(order.status).toBe('partially_refunded');
  });
});

3. State Analysis

Debug complex state management:

// AI: Analyze Redux state changes
const orderReducer = (state = initialState, action) => {
  switch (action.type) {
    case 'ORDER_CREATED':
      return {
        ...state,
        orders: [...state.orders, action.payload],
        loading: false
      };
      
    case 'ORDER_UPDATED':
      // AI will suggest immutable update pattern
      return {
        ...state,
        orders: state.orders.map(order =>
          order.id === action.payload.id
            ? { ...order, ...action.payload }
            : order
        )
      };
      
    default:
      return state;
  }
};

Best Practices

  1. Systematic Approach

    • Start with error messages
    • Check recent changes
    • Test assumptions
    • Use AI analysis

  2. Debugging Environment

    // AI: Set up debugging environment
const debugConfig = {
  logLevel: 'debug',
  errorReporting: true,
  performance: true,
  network: true
};

  3. Documentation

    // AI: Document debugging steps
/**
 * Bug: Order total calculation incorrect
 * Steps to reproduce:
 * 1. Create order with multiple items
 * 2. Apply discount code
 * 3. Check final total
 * 
 * Root cause: Discount applied twice
 * Fix: Update order calculation logic
 */

Troubleshooting Common Issues

1. Async Debugging

// AI: Debug async flow
async function debugAsync() {
  console.log('Start');
  try {
    const result = await Promise.all([
      asyncOperation1(),
      asyncOperation2()
    ]);
    console.log('Result:', result);
  } catch (error) {
    console.error('Error in async operations:', error);
  }
}

2. React Component Debugging

// AI: Debug component updates
function DebugComponent({ data }) {
  useEffect(() => {
    console.log('Component mounted');
    return () => console.log('Component unmounted');
  }, []);
  
  useEffect(() => {
    console.log('Data changed:', data);
  }, [data]);
  
  return <div>{/* Component content */}</div>;
}

Next Steps

  1. Practice with real bugs
  2. Learn advanced debugging patterns
  3. Create custom debugging tools
  4. Explore Performance Optimization

Remember: Effective debugging is a combination of systematic approach, proper tools, and experience. AI can help accelerate the process, but understanding the underlying issues is crucial.