Preparing for PHP Developer role at Wieni

JIT (Just-In-Time) compilation in PHP 8 converts PHP opcodes into machine code at runtime. It works alongside OpCache and has two modes: tracing JIT and function JIT. The JIT compiler is most beneficial for CPU-intensive tasks and mathematical computations, rather than I/O-bound operations typical in web applications. Given that the role mentions high-performance applications, understanding JIT is crucial for optimizing computation-heavy backend processes. For example, if working with VRT or Studio 100's media processing, JIT could significantly improve performance for video/audio processing algorithms.

Named arguments allow specifying only required parameters in function calls by explicitly naming them, regardless of their order. For example:

public function processMedia(string $format, ?array $options = null, bool $async = false) {}

// Using named arguments
processMedia(async: true, format: 'mp4');

This improves code readability by making function calls self-documenting, especially useful in complex systems like those mentioned in the job description where multiple developers need to maintain the code. Since the company values efficient communication, named arguments serve as a form of self-documentation.

OpCache improves performance by storing precompiled script bytecode in memory, eliminating the need for PHP to load and parse scripts on every request. It works in three main steps:

1. Compiles PHP code into opcodes
2. Stores these opcodes in shared memory
3. Reuses the cached opcodes for subsequent requests

For high-traffic applications like De Tijd or BRUZZ (mentioned in the job description), OpCache can significantly reduce server load and response times. Important to note that proper OpCache configuration is crucial for optimal performance, including settings like opcache.revalidate_freq and opcache.memory_consumption.

Weak references allow referencing objects without preventing them from being garbage collected, unlike regular references which keep objects in memory. Example:

$object = new HeavyObject();
$weakref = WeakReference::create($object);
unset($object);
// $weakref->get() will return null as the object can be garbage collected

This is particularly useful in caching systems (mentioned as daily business in the job description) to prevent memory leaks while maintaining reference relationships. It's also valuable for implementing observer patterns in event-driven architectures without causing memory leaks.

Union types allow declaring multiple allowed types for properties, parameters, and return values:

public function processContent(int|string $content): array|false {
    // Implementation
}

This enhances type safety while maintaining flexibility, which is crucial when working with diverse data sources (like in VRT or DNS Belgium projects mentioned in the description). Union types reduce the need for docblock annotations and provide better IDE support, making the code more maintainable and self-documenting.

Attributes provide a native way to add metadata to classes, methods, properties, and functions using a standardized syntax:

#[Route("/api/media", methods: ["GET"])]
#[Cache(expires: "1h")]
public function getMedia() {}

They replace traditional docblock annotations with native PHP syntax, providing better type safety and validation. This is particularly relevant for Symfony applications (mentioned as a required skill) where attributes are extensively used for routing, validation, and ORM mappings.

Match expressions are more concise and safer than switch statements. Key differences:

1. Match does strict comparison (===)
2. Match is an expression that returns a value
3. Match requires all cases to be covered

$result = match ($status) {
    200, 201 => 'success',
    400, 401, 403 => 'client error',
    500 => 'server error',
    default => 'unknown status'
};

This makes code more reliable and reduces potential bugs, which is crucial for maintaining high-quality applications like those mentioned in the job description for UZ Leuven or De Tijd.

For a high-traffic news website like VRT or De Tijd (mentioned in the job description), I would implement a multi-layered caching strategy:

1. CDN Layer: For static assets and full-page caching
2. Application Layer:
   • Redis for dynamic content with TTL-based invalidation
   • Fragment caching for reusable components
   • ESI (Edge Side Includes) for personalized content
3. Database Layer:
   • Query cache for frequently accessed data
   • ORM result cache for complex queries

Key considerations:

• Short TTL for breaking news (1-5 minutes)
• Longer TTL for archival content (1 hour to 1 day)
• Varnish for full-page caching with custom VCL rules
• Implement cache tags for precise invalidation

For distributed system cache invalidation, I would implement:

1. Event-based invalidation:

   • Use message queues (RabbitMQ) for broadcasting cache invalidation events
   • Implement the Publisher/Subscriber pattern for cache updates

2. Pattern-based invalidation:

   • Use cache tags for grouping related items
   • Implement versioning for cache keys

3. Selective invalidation strategies:

   • Time-based (TTL) for less critical data
   • Manual purge for urgent updates
   • Soft invalidation (serve stale while revalidating)

Example implementation with Redis:

class CacheInvalidator {
    public function invalidateByPattern(string $pattern): void {
        $keys = $this->redis->keys($pattern);
        $this->redis->del($keys);
        $this->messageQueue->publish('cache.invalidated', [
            'pattern' => $pattern,
            'timestamp' => time()
        ]);
    }
}

Key differences and use cases:

Redis:

• Data persistence
• Complex data structures (lists, sets, sorted sets)
• Built-in pub/sub messaging
• Perfect for session storage, queues, and real-time analytics
• Better for complex caching scenarios mentioned in the job description

Memcached:

• Simpler, purely in-memory storage
• Better for simple key-value storage
• Lower memory overhead
• Multi-thread architecture

Use Redis when:

• Need for data persistence
• Complex data structures required
• Building real-time features
• Need for atomic operations

Use Memcached when:

• Simple caching requirements
• Large cache size needed
• Maximum memory efficiency is crucial
• Simple scaling requirements

In Symfony, I would implement page caching through multiple approaches:

1. HTTP Cache (using attributes):

#[Cache(public: true, maxage: 3600, smaxage: 7200)]
public function showArticle(string $slug): Response
{
    // Controller logic
}

2. Reverse Proxy Integration:

# config/packages/framework.yaml
framework:
    cache:
        app: cache.adapter.redis
        system: cache.adapter.system

3. ESI for dynamic parts:

{{ render_esi(controller('App\\Controller\\PartialController::widget')) }}

4. Custom Cache Service:

class PageCache
{
    public function __construct(
        private TagAwareCacheInterface $cache,
        private EventDispatcherInterface $dispatcher
    ) {}

    public function getCachedPage(string $key, callable $regenerator): Response
    {
        return $this->cache->get($key, $regenerator);
    }
}

Cache stampede (also known as cache thundering herd) occurs when multiple requests attempt to regenerate the same cached content simultaneously after it expires.

Prevention strategies:

1. Probabilistic early expiration:

public function get(string $key): mixed
{
    $value = $this->cache->get($key);
    $timeout = $this->cache->getTTL($key);
    
    if ($value && $timeout < 300 && random_int(1, 100) <= 10) {
        // 10% chance to regenerate early
        return $this->regenerateCache($key);
    }
    
    return $value;
}

2. Lock-based prevention:

public function getWithLock(string $key): mixed
{
    $lock = $this->cache->lock($key, 10);
    
    if ($lock->acquire()) {
        try {
            return $this->regenerateCache($key);
        } finally {
            $lock->release();
        }
    }
    
    return $this->cache->get($key);
}

3. Stale-while-revalidate pattern implementation

Cache warming is the process of pre-populating cache before it's needed in production. It's crucial for performance-critical applications mentioned in the job description.

Implementation example:

class CacheWarmer implements CacheWarmerInterface
{
    public function warmUp(string $cacheDir): array
    {
        // Warm up frequently accessed data
        $this->warmUpHomePage();
        $this->warmUpCategories();
        $this->warmUpPopularContent();
        
        return ['cache.popular_items', 'cache.categories'];
    }
    
    public function isOptional(): bool
    {
        return false;
    }
}

Benefits:

1. Prevents cold starts after deployments
2. Ensures consistent performance
3. Reduces initial user wait times
4. Prevents cache stampede during high-traffic periods

For large-scale applications like those mentioned in the job description (VRT, De Tijd), I would implement:

1. Client-side caching:

public function setResponseHeaders(Response $response): void
{
    $response->headers->set('Cache-Control', 'public, max-age=3600');
    $response->setEtag(md5($response->getContent()));
}

2. Application caching layers:

class MultilayerCache
{
    public function get(string $key): mixed
    {
        // L1: Local in-memory cache
        if ($value = $this->localCache->get($key)) {
            return $value;
        }
        
        // L2: Redis cache
        if ($value = $this->redis->get($key)) {
            $this->localCache->set($key, $value);
            return $value;
        }
        
        // L3: Database cache
        return $this->databaseCache->get($key);
    }
}

3. Infrastructure layers:

• Varnish for full-page caching
• CDN for static assets
• Redis for session and dynamic data
• Database query cache

Key considerations:

• Cache coherency between layers
• Proper invalidation strategy
• Monitoring and metrics
• Fallback mechanisms

The Service Container (or Dependency Injection Container) is a central component in Symfony that manages service instantiation and dependencies. It works by:

1. Reading service definitions from configuration (YAML/XML/PHP)
2. Managing service lifecycle (singleton/transient)
3. Automatically injecting dependencies
4. Providing lazy loading capabilities

Key benefits include:

• Reduced coupling between components
• Easier testing through dependency injection
• Performance optimization through shared services
• Automatic dependency resolution

For high-performance applications like those mentioned in the job description (VRT, De Tijd), the service container's lazy loading and caching capabilities are crucial for maintaining optimal performance under heavy load.

The Event Dispatcher implements the Observer pattern and allows for loose coupling between components. It works through:

1. Event Classes: Hold event-specific data
2. Listeners/Subscribers: React to events
3. Dispatcher: Manages event distribution

Common use cases:

• Logging system actions
• Cache invalidation
• User authentication events
• Custom business logic hooks

For media-heavy applications like BRUZZ or Studio 100 (mentioned in job description), you might use events for:

• Media file processing
• Content cache invalidation
• User activity tracking
• Async job processing

Example:

class ContentUpdateListener
{
    public function onContentUpdate(ContentUpdateEvent $event): void
    {
        // Invalidate cache
        // Notify other services
        // Update search index
    }
}

Custom middleware in Symfony can be implemented in several ways:

1. Event Listeners:

class ApiMiddleware implements EventSubscriberInterface
{
    public static function getSubscribedEvents()
    {
        return [
            KernelEvents::REQUEST => ['onKernelRequest', 1],
        ];
    }
}

2. Request Subscribers:

class PerformanceMiddleware implements EventSubscriberInterface
{
    public function onKernelRequest(RequestEvent $event)
    {
        // Add performance headers
        // Check rate limits
        // Validate API tokens
    }
}

This is particularly relevant for high-traffic applications like VRT or De Tijd, where you might need middleware for:

• Rate limiting
• Performance monitoring
• Authentication
• Request/Response transformation

Following Symfony's best practices and modern PHP standards:

1. Service Layer Organization:

• Services/ - Business logic
• Repository/ - Data access
• EventListener/ - Event handlers
• Controller/ - Thin controllers
• DTO/ - Data transfer objects

2. Implementation Guidelines:

// Service class example
class ArticleService
{
    public function __construct(
        private ArticleRepository $repository,
        private CacheInterface $cache,
        private EventDispatcherInterface $dispatcher
    ) {}

    public function publish(Article $article): void
    {
        // Business logic
        $this->dispatcher->dispatch(new ArticlePublishedEvent($article));
    }
}

3. Best Practices:

• Use constructor injection
• Keep controllers thin
• Implement command/query separation
• Use DTOs for data transfer

Symfony's cache component uses a flexible system with multiple adapters and pools:

1. Core Components:

• Cache Items
• Cache Pools
• Cache Adapters (Redis, Memcached, FileSystem)

2. Implementation:

class ContentCache
{
    public function __construct(
        private CacheItemPoolInterface $cache
    ) {}

    public function getCachedContent(string $key): mixed
    {
        return $this->cache->get($key, function(ItemInterface $item) {
            $item->expiresAfter(3600);
            return $this->computeContent();
        });
    }
}

3. Features:

• Tag-based invalidation
• Hierarchical caching
• Early expiration
• Cache stampede protection

This is especially relevant for high-traffic news websites like BRUZZ or De Tijd where efficient caching is crucial.

Symfony's security component provides a comprehensive authentication and authorization system:

1. Authentication Process:

security:
    providers:
        app_user_provider:
            entity:
                class: App\Entity\User
                property: email
    firewalls:
        main:
            lazy: true
            provider: app_user_provider
            custom_authenticator: App\Security\CustomAuthenticator

2. Key Components:

• Security Guards
• Voters
• Password Hashers
• User Providers

3. Authentication Flow:

• Request intercepted by firewall
• Authenticator processes credentials
• Token creation and storage
• User object population

For applications like UZ Leuven (healthcare) mentioned in the job description, security is crucial, requiring:

• Strong authentication
• Role-based access control
• Session management
• Audit logging

I would implement the Repository pattern as follows:

interface UserRepositoryInterface {
    public function find(int $id): ?User;
    public function findAll(): array;
    public function save(User $user): void;
}

class UserRepository implements UserRepositoryInterface {
    private PDO $connection;
    
    public function __construct(PDO $connection) {
        $this->connection = $connection;
    }
    
    public function find(int $id): ?User {
        $stmt = $this->connection->prepare('SELECT * FROM users WHERE id = :id');
        $stmt->execute(['id' => $id]);
        $data = $stmt->fetch(PDO::FETCH_ASSOC);
        
        return $data ? new User($data) : null;
    }
    
    // Other method implementations...
}

This implementation follows PHP 8.3's strict typing and provides a clear separation between the domain model and data mapping layers, which is crucial for maintaining high-performance applications as mentioned in the job requirements.

Here's how I would implement the Strategy pattern for payment processing:

interface PaymentStrategyInterface {
    public function pay(float $amount): bool;
}

class CreditCardPayment implements PaymentStrategyInterface {
    public function pay(float $amount): bool {
        // Credit card processing logic
        return true;
    }
}

class PayPalPayment implements PaymentStrategyInterface {
    public function pay(float $amount): bool {
        // PayPal processing logic
        return true;
    }
}

class PaymentProcessor {
    private PaymentStrategyInterface $paymentStrategy;
    
    public function setPaymentStrategy(PaymentStrategyInterface $strategy): void {
        $this->paymentStrategy = $strategy;
    }
    
    public function processPayment(float $amount): bool {
        return $this->paymentStrategy->pay($amount);
    }
}

This pattern allows for easy extension when adding new payment methods, following the Open-Closed Principle of SOLID. It's particularly relevant for web applications handling various payment methods, as mentioned in the job description for clients like UZ Leuven and Joker Reizen.

The Observer pattern facilitates loose coupling by allowing objects to communicate without explicit knowledge of each other:

interface SubjectInterface {
    public function attach(ObserverInterface $observer): void;
    public function detach(ObserverInterface $observer): void;
    public function notify(): void;
}

interface ObserverInterface {
    public function update(SubjectInterface $subject): void;
}

class UserManager implements SubjectInterface {
    private array $observers = [];
    
    public function attach(ObserverInterface $observer): void {
        $this->observers[] = $observer;
    }
    
    public function createUser(User $user): void {
        // User creation logic
        $this->notify();
    }
    
    public function notify(): void {
        foreach ($this->observers as $observer) {
            $observer->update($this);
        }
    }
}

This pattern is particularly useful in web applications where multiple systems need to react to events (like in VRT or BRUZZ media platforms mentioned in the job description) while maintaining high performance and scalability.

The Dependency Inversion Principle states that high-level modules should not depend on low-level modules; both should depend on abstractions. Here's an implementation:

// Instead of this:
class UserService {
    private MySQLDatabase $database;
    
    public function __construct() {
        $this->database = new MySQLDatabase();
    }
}

// Do this:
interface DatabaseInterface {
    public function query(string $sql): array;
}

class UserService {
    private DatabaseInterface $database;
    
    public function __construct(DatabaseInterface $database) {
        $this->database = $database;
    }
}

This approach aligns with Symfony's service container and dependency injection practices, which are crucial skills mentioned in the job description. It also makes the code more testable and maintainable.

To refactor a God Object, I would:

1. Identify distinct responsibilities
2. Extract them into separate classes
3. Use dependency injection

Example:

// Before: God Object
class UserManager {
    public function createUser() { /* ... */ }
    public function sendEmail() { /* ... */ }
    public function generateReport() { /* ... */ }
    public function processPayment() { /* ... */ }
}

// After: Separated responsibilities
class UserService {
    public function __construct(
        private EmailService $emailService,
        private ReportGenerator $reportGenerator,
        private PaymentProcessor $paymentProcessor
    ) {}
    
    public function createUser(User $user): void {
        // User creation logic
        $this->emailService->sendWelcomeEmail($user);
    }
}

This refactoring approach is especially relevant for maintaining large-scale web applications like those mentioned in the job description (VRT, DNS Belgium, etc.).

Here's how I would implement the Command pattern for async processing:

interface CommandInterface {
    public function execute(): void;
}

class SendEmailCommand implements CommandInterface {
    public function __construct(
        private string $to,
        private string $subject,
        private string $body
    ) {}
    
    public function execute(): void {
        // Email sending logic
    }
}

class AsyncCommandBus {
    private RedisClient $redis;
    
    public function dispatch(CommandInterface $command): void {
        $this->redis->lpush('commands', serialize($command));
    }
}

class CommandWorker {
    public function process(): void {
        while (true) {
            $command = unserialize($this->redis->rpop('commands'));
            if ($command instanceof CommandInterface) {
                $command->execute();
            }
        }
    }
}

This implementation is particularly relevant for high-performance applications mentioned in the job description, using Redis for queue management and ensuring efficient processing of background tasks.

For complex service classes, I follow several key approaches:

1. Use Dependency Injection to make services testable:

class NewsService {
    public function __construct(
        private readonly CacheInterface $cache,
        private readonly DatabaseInterface $db,
        private readonly LoggerInterface $logger
    ) {}
}

2. Create test doubles using PHPUnit's MockBuilder:

public function setUp(): void {
    $this->cache = $this->createMock(CacheInterface::class);
    $this->db = $this->createMock(DatabaseInterface::class);
    $this->logger = $this->createMock(LoggerInterface::class);
    $this->service = new NewsService($this->cache, $this->db, $this->logger);
}

3. Test each dependency interaction separately
4. Use data providers for different scenarios
5. Implement integration tests for critical paths

Mocks and stubs serve different testing purposes:

Stubs:

• Provide predefined responses to calls
• Used when you need to simulate a dependency's behavior
• Don't verify interactions

$cacheStub = $this->createStub(CacheInterface::class);
$cacheStub->method('get')->willReturn('cached_value');

Mocks:

• Verify that specific methods are called with expected parameters
• Used when testing behavior and interactions
• Can enforce expectations about method calls

$cacheMock = $this->createMock(CacheInterface::class);
$cacheMock->expects($this->once())
    ->method('set')
    ->with('key', 'value', 3600);

Use stubs when you just need data, use mocks when you need to verify interactions.

For testing async operations, I would:

1. Use PHPUnit's built-in async testing capabilities:

public function testAsyncOperation(): void {
    $promise = $this->asyncService->processJob();
    $this->assertInstanceOf(PromiseInterface::class, $promise);
    
    $result = await($promise);
    $this->assertEquals('expected', $result);
}

2. For Swoole/RoadRunner implementations:

• Use dedicated testing frameworks that support async operations
• Implement proper test doubles for async services
• Test both success and failure scenarios

3. For queue-based async operations:

• Mock queue services
• Test job dispatch and handling separately
• Verify job payload structure

Given that caching is mentioned as "daily business" in the job description, here's my comprehensive approach:

1. Test Cache Interface Implementation:

public function testCacheOperations(): void {
    $cache = new RedisCache($this->redis);
    
    $cache->set('key', 'value', 3600);
    $this->assertEquals('value', $cache->get('key'));
    
    $cache->delete('key');
    $this->assertNull($cache->get('key'));
}

2. Test Cache Strategies:

• Test cache hits/misses
• Verify TTL functionality
• Test cache invalidation
• Test cache warming scenarios

3. Test Edge Cases:

• Cache stampede prevention
• Race conditions
• Memory limits
• Network failures

4. Integration Tests:

• Test with actual cache servers in staging
• Performance testing under load

To ensure test isolation:

1. Use setUp() and tearDown():

protected function setUp(): void {
    $this->cache = new ArrayCache();
    $this->db = new TestDatabase();
}

protected function tearDown(): void {
    $this->cache->clear();
    $this->db->rollback();
}

2. Use database transactions:

public function setUp(): void {
    $this->connection->beginTransaction();
}

public function tearDown(): void {
    $this->connection->rollBack();
}

3. Use separate test databases
4. Implement test fixtures
5. Reset static properties
6. Use @preserveGlobalState annotation
7. Implement proper dependency injection

For testing API endpoints, especially considering the web applications mentioned in the job description:

1. Functional Tests:

public function testNewsEndpoint(): void {
    $client = static::createClient();
    $client->request('GET', '/api/news');
    
    $this->assertResponseIsSuccessful();
    $this->assertJsonStructure(['data', 'meta']);
}

2. Test Different Response Codes:

• 200 Success scenarios
• 400 Bad request handling
• 401/403 Authorization
• 404 Not found
• 500 Server errors

3. Test Data Validation:

• Input validation
• Response format
• Data transformation

4. Performance Testing:

• Response times
• Cache headers
• Rate limiting

5. Authentication Testing:

• Token validation
• Permission checks
• Session handling