// Example: Ask ChatGPT to create a validation function
// Prompt: "Create a comprehensive email validation function in JavaScript"

function validateEmail(email) {
    const emailRegex = /^[^\s@] @[^\s@] \.[^\s@] $/;
    
    if (!email) return { isValid: false, error: 'Email is required' };
    if (typeof email !== 'string') return { isValid: false, error: 'Email must be a string' };
    if (!emailRegex.test(email)) return { isValid: false, error: 'Invalid email format' };
    if (email.length > 254) return { isValid: false, error: 'Email too long' };
    
    const [localPart, domain] = email.split('@');
    if (localPart.length > 64) return { isValid: false, error: 'Local part too long' };
    
    return { isValid: true, error: null };
}

// تست تابع
console.log(validateEmail('test@example.com')); // { isValid: true, error: null }
console.log(validateEmail('invalid-email'));    // { isValid: false, error: 'Invalid email format' }

# Example: Bug detection and fixing with ChatGPT
Problematic code:

def calculate_discount(price, discount_percent):
    return price - (price * discount_percent)

After debugging with ChatGPT:

def calculate_discount(price, discount_percent):
    """
    Calculate final price after applying discount
    
    Args:
        price (float): Original price
        discount_percent (float): Discount percentage (0-100)
    
    Returns:
        float: Final price after discount
    """
    if not isinstance(price, (int, float)) or price < 0:
        raise ValueError("Price must be a non-negative number")
    
    if not isinstance(discount_percent, (int, float)) or not (0 <= discount_percent <= 100):
        raise ValueError("Discount percent must be between 0 and 100")
    
    discount_amount = price * (discount_percent / 100)
    return max(0, price - discount_amount)

# In VS Code, from the Extensions Marketplace
Search for "GitHub Copilot" and install


Or via the Command Palette:

Ctrl   Shift   P → "Extensions: Install Extensions" → "GitHub Copilot"

// Example: Creating a React component with Copilot
// Start typing:
function UserProfile({ user, onUpdate }) {
    // Copilot suggests:
    const [isEditing, setIsEditing] = useState(false);
    const [formData, setFormData] = useState(user);
    
    const handleSubmit = (e) => {
        e.preventDefault();
        onUpdate(formData);
        setIsEditing(false);
    };
    
    const handleChange = (field, value) => {
        setFormData(prev => ({ ...prev, [field]: value }));
    };
    
    if (isEditing) {
        return (
            <form onSubmit={handleSubmit} className="user-profile-form">
                <input
                    type="text"
                    value={formData.name}
                    onChange={(e) => handleChange('name', e.target.value)}
                    placeholder="Full Name"
                />
                <input
                    type="email"
                    value={formData.email}
                    onChange={(e) => handleChange('email', e.target.value)}
                    placeholder="Email"
                />
                <div className="form-actions">
                    <button type="submit">Save</button>
                    <button type="button" onClick={() => setIsEditing(false)}>
                        Cancel
                    </button>
                </div>
            </form>
        );
    }
    
    return (
        <div className="user-profile">
            <h2>{user.name}</h2>
            <p>{user.email}</p>
            <button onClick={() => setIsEditing(true)}>Edit Profile</button>
        </div>
    );
}

// Example: Generating Unit Tests with Copilot
// For the validateEmail function we created earlier:

describe('validateEmail', () => {
    test('should validate correct email formats', () => {
        expect(validateEmail('test@example.com').isValid).toBe(true);
        expect(validateEmail('user.name@domain.co.uk').isValid).toBe(true);
        expect(validateEmail('user tag@domain.org').isValid).toBe(true);
    });
    
    test('should reject invalid email formats', () => {
        expect(validateEmail('invalid-email').isValid).toBe(false);
        expect(validateEmail('user@').isValid).toBe(false);
        expect(validateEmail('@domain.com').isValid).toBe(false);
        expect(validateEmail('user@domain').isValid).toBe(false);
    });
    
    test('should handle edge cases', () => {
        expect(validateEmail('').isValid).toBe(false);
        expect(validateEmail(null).isValid).toBe(false);
        expect(validateEmail(undefined).isValid).toBe(false);
        expect(validateEmail(123).isValid).toBe(false);
        
        // Test email length limits
        const longEmail = 'a'.repeat(64)   '@'   'b'.repeat(189)   '.com';
        expect(validateEmail(longEmail).isValid).toBe(false);
    });
});

# Example: gitlab-ci.yml with AI integration
stages:
  - code-review
  - test
  - security-scan
  - deploy

ai_code_review:
  stage: code-review
  image: node:16
  script:
    - |
      # Automated code analysis with AI
      npx ai-code-analyzer --pattern "security,performance,best-practices"
      npx copilot-suggestions --format "markdown"
  artifacts:
    paths:
      - ai-review-report.md

auto_test_generation:
  stage: test
  script:
    - |
      # Automatic test generation for new code
      npx ai-test-generator --coverage 80
      npm run test:coverage

security_ai_scan:
  stage: security-scan
  script:
    - |
      # Advanced security scanning with AI
      npx ai-security-scanner --deep-scan
      npx vulnerability-predictor --model "latest"

deploy_with_ai_optimization:
  stage: deploy
  script:
    - |
      # Optimize deployment settings with AI
      npx ai-deploy-optimizer --platform "kubernetes"
      kubectl apply -f optimized-deployment.yaml

# Example: Using OpenAI API for code analysis
import openai
import ast

class CodeAnalyzer:
    def __init__(self, api_key):
        self.client = openai.OpenAI(api_key=api_key)
    
    def analyze_code_quality(self, code_snippet):
        prompt = f"""
        Analyze this code for quality issues and suggest improvements:
        
        {code_snippet}
        
        Provide analysis in this format:
        1. Code Quality Score: /10
        2. Potential Issues: 
        3. Security Concerns:
        4. Performance Suggestions:
        5. Best Practices Recommendations:
        """
        
        response = self.client.chat.completions.create(
            model="gpt-4",
            messages=[{"role": "user", "content": prompt}],
            temperature=0.3
        )
        
        return response.choices[0].message.content
    
    def generate_optimized_version(self, original_code):
        prompt = f"""
        Optimize this code for better performance and maintainability:
        
        {original_code}
        
        Provide the optimized version with comments explaining changes.
        """
        
        response = self.client.chat.completions.create(
            model="gpt-4",
            messages=[{"role": "user", "content": prompt}],
            temperature=0.2
        )
        
        return response.choices[0].message.content

استفاده عملی

analyzer = CodeAnalyzer("your-api-key")
result = analyzer.analyze_code_quality("""
def process_data(data):
    result = []
    for i in range(len(data)):
        if data[i] > 10:
            result.append(data[i] * 2)
    return result
""")
print(result)

// Example: Detecting errors in AI-generated code
// AI-generated code (problematic):
function findUser(users, id) {
    return users.find(user => user.id === id) || 'User not found';
}

// Problems:
// 1. Incompatible return type (sometimes object, sometimes string)
// 2. Possible error if users is null or undefined
// 3. No type checking of parameters

// Fixed version:
function findUser(users, id) {
    if (!Array.isArray(users)) {
        throw new TypeError('Users must be an array');
    }
    
    if (typeof id !== 'number' && typeof id !== 'string') {
        throw new TypeError('ID must be a number or string');
    }
    
    const user = users.find(user => user.id == id); // Use loose equality for flexibility
    
    if (!user) {
        throw new Error(User with ID ${id} not found);
    }
    
    return user;
}

# نمونه‌ای از ابزارهای آینده
class AIDeveloperAssistant:
    def predict_next_feature(self, codebase, user_behavior):
        """Predicting the next feature based on codebase analysis and user behavior"""
        pass
    
    def auto_refactor(self, code, target_metrics):
        """Automatic code rewrite to achieve specific metrics"""
        pass
    
    def generate_documentation(self, code, style_guide):
        """Producing documentation based on code and style guide"""
        pass