// Comment: Create a function to validate email addresses
// AI-generated code:
function validateEmail(email) {
  const emailRegex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
  return emailRegex.test(email);
}
 
// Comment: Create a debounced search function
// AI-generated code:
function createDebouncedSearch(searchFunction, delay = 300) {
  let timeoutId;
  return function(...args) {
    clearTimeout(timeoutId);
    timeoutId = setTimeout(() => searchFunction.apply(this, args), delay);
  };
}

// AI can generate comprehensive test cases
describe('User Authentication', () => {
  test('should validate correct email format', () => {
    expect(validateEmail('user@example.com')).toBe(true);
    expect(validateEmail('invalid-email')).toBe(false);
  });
 
  test('should handle edge cases', () => {
    expect(validateEmail('')).toBe(false);
    expect(validateEmail('user@')).toBe(false);
    expect(validateEmail('@example.com')).toBe(false);
  });
});

// AI-powered form validation that learns from user behavior
const SmartForm = () => {
  const [formData, setFormData] = useState({});
  const [aiSuggestions, setAiSuggestions] = useState({});
 
  const handleInputChange = async (field, value) => {
    setFormData(prev => ({ ...prev, [field]: value }));
    
    // AI analyzes input patterns and suggests improvements
    const suggestions = await aiValidationService.analyze(field, value, formData);
    setAiSuggestions(prev => ({ ...prev, [field]: suggestions }));
  };
 
  return (
    <form>
      <input
        type="email"
        onChange={(e) => handleInputChange('email', e.target.value)}
        placeholder="Enter your email"
      />
      {aiSuggestions.email && (
        <div className="ai-suggestion">
          💡 {aiSuggestions.email}
        </div>
      )}
    </form>
  );
};

// AI-driven content personalization
const PersonalizedDashboard = ({ userId }) => {
  const [personalizedContent, setPersonalizedContent] = useState([]);
 
  useEffect(() => {
    // AI analyzes user behavior and preferences
    aiPersonalizationEngine.getRecommendations(userId)
      .then(content => setPersonalizedContent(content));
  }, [userId]);
 
  return (
    <div className="dashboard">
      {personalizedContent.map(item => (
        <ContentCard
          key={item.id}
          content={item}
          relevanceScore={item.aiScore}
        />
      ))}
    </div>
  );
};

// AI-powered bundle optimization
const aiOptimizedWebpack = {
  optimization: {
    splitChunks: {
      chunks: 'all',
      cacheGroups: {
        // AI determines optimal chunk splitting
        vendor: {
          test: /[\\/]node_modules[\\/]/,
          name: 'vendors',
          chunks: 'all',
          priority: aiChunkAnalyzer.calculatePriority()
        }
      }
    }
  }
};
 
// AI-driven lazy loading
const SmartLazyLoader = ({ children }) => {
  const [shouldLoad, setShouldLoad] = useState(false);
  const elementRef = useRef();
 
  useEffect(() => {
    const observer = new IntersectionObserver(
      ([entry]) => {
        // AI predicts user behavior to preload content
        const loadProbability = aiPredictor.calculateLoadProbability(
          entry.intersectionRatio,
          userBehaviorData
        );
        
        if (loadProbability > 0.7) {
          setShouldLoad(true);
        }
      },
      { threshold: 0.1 }
    );
 
    if (elementRef.current) {
      observer.observe(elementRef.current);
    }
 
    return () => observer.disconnect();
  }, []);
 
  return (
    <div ref={elementRef}>
      {shouldLoad ? children : <div>Loading...</div>}
    </div>
  );
};

# AI-optimized CI/CD pipeline
name: Smart Deployment
on:
  push:
    branches: [main]
 
jobs:
  ai-analysis:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: AI Code Analysis
        run: |
          # AI analyzes code changes and predicts impact
          ai-analyzer --predict-impact --suggest-tests
      
      - name: Smart Test Selection
        run: |
          # AI selects relevant tests based on code changes
          ai-test-selector --optimize-for-speed
      
      - name: Intelligent Deployment
        run: |
          # AI determines optimal deployment strategy
          ai-deployer --strategy=auto --monitor=true

/**
 * AI-generated documentation
 * This function calculates the optimal cache strategy for API responses
 * based on usage patterns and data freshness requirements.
 * 
 * @param {Object} apiEndpoint - The API endpoint configuration
 * @param {Array} usagePatterns - Historical usage data
 * @param {Number} freshnessThreshold - Maximum acceptable data age in minutes
 * @returns {Object} Optimized caching strategy
 * 
 * @example
 * const strategy = calculateCacheStrategy(
 *   { url: '/api/users', method: 'GET' },
 *   userAccessPatterns,
 *   30
 * );
 */
function calculateCacheStrategy(apiEndpoint, usagePatterns, freshnessThreshold) {
  // AI analyzes patterns and generates optimal caching strategy
  return aiCacheOptimizer.analyze(apiEndpoint, usagePatterns, freshnessThreshold);
}

// AI monitors application health and auto-fixes issues
const SelfHealingApp = () => {
  useEffect(() => {
    const healthMonitor = new AIHealthMonitor({
      onError: (error, context) => {
        // AI analyzes error and attempts automatic fix
        aiErrorResolver.resolve(error, context)
          .then(fix => {
            console.log('Auto-applied fix:', fix);
            // Apply fix automatically
            applyFix(fix);
          })
          .catch(() => {
            // Escalate to human developers if AI can't fix
            notifyDevelopers(error, context);
          });
      },
      onPerformanceIssue: (metrics) => {
        // AI optimizes performance in real-time
        aiPerformanceOptimizer.optimize(metrics);
      }
    });
 
    healthMonitor.start();
    return () => healthMonitor.stop();
  }, []);
 
  return <App />;
};

// AI predicts user needs and preloads content
const PredictiveUX = () => {
  const [predictedActions, setPredictedActions] = useState([]);
 
  useEffect(() => {
    // AI analyzes user behavior patterns
    aiUXPredictor.predictNextActions(userBehaviorHistory)
      .then(predictions => {
        setPredictedActions(predictions);
        
        // Preload predicted content
        predictions.forEach(action => {
          if (action.probability > 0.8) {
            preloadContent(action.target);
          }
        });
      });
  }, [userBehaviorHistory]);
 
  return (
    <div>
      {/* Show predicted shortcuts */}
      <div className="ai-suggestions">
        {predictedActions.map(action => (
          <button
            key={action.id}
            onClick={() => executeAction(action)}
            className="prediction-button"
          >
            {action.label} ({Math.round(action.probability * 100)}%)
          </button>
        ))}
      </div>
    </div>
  );
};

// AI must be trained to avoid security vulnerabilities
const secureAIGeneration = {
  rules: [
    'Never hardcode sensitive data',
    'Always validate user input',
    'Use parameterized queries',
    'Implement proper authentication',
    'Follow OWASP guidelines'
  ],
  
  validate: (generatedCode) => {
    return securityAnalyzer.scan(generatedCode);
  }
};

// Begin with simple AI integrations
import { aiCodeSuggestions } from 'ai-dev-tools';
 
const CodeEditor = () => {
  const [code, setCode] = useState('');
  const [suggestions, setSuggestions] = useState([]);
 
  const handleCodeChange = async (newCode) => {
    setCode(newCode);
    
    // Get AI suggestions for improvements
    const aiSuggestions = await aiCodeSuggestions.analyze(newCode);
    setSuggestions(aiSuggestions);
  };
 
  return (
    <div>
      <textarea
        value={code}
        onChange={(e) => handleCodeChange(e.target.value)}
      />
      <div className="suggestions">
        {suggestions.map(suggestion => (
          <div key={suggestion.id} className="suggestion">
            {suggestion.message}
          </div>
        ))}
      </div>
    </div>
  );
};

// Structure your app to be AI-friendly
const AIReadyApp = () => {
  return (
    <div>
      {/* Semantic HTML for better AI understanding */}
      <header role="banner">
        <nav aria-label="Main navigation">
          {/* Clear, semantic navigation */}
        </nav>
      </header>
      
      <main role="main">
        {/* Well-structured content */}
        <article>
          <h1>Clear, descriptive headings</h1>
          <p>Meaningful content with proper context</p>
        </article>
      </main>
      
      {/* AI-friendly data attributes */}
      <div data-ai-component="user-dashboard" data-ai-context="analytics">
        {/* Component content */}
      </div>
    </div>
  );
};