Preparing for Mid-Senior PHP Developer - Symfony role at MeritStory

Return type declarations provide several key benefits:

1. Enhanced Code Reliability: They ensure functions return expected data types, reducing runtime errors
2. Better Static Analysis: Tools can detect type-related issues before execution
3. Improved Documentation: Code becomes self-documenting
4. Contract Enforcement: Creates a strict contract for function behavior

Example:

public function calculateUserMerit(): float {
    // Type enforcement ensures this always returns a float
    return $this->meritPoints * $this->multiplier;
}

This aligns with MeritStory's emphasis on high-quality code and attention to detail.

Union Types (|) allow a value to be one of several types:

public function processApiResponse(array|string $response): int|null {
    // Handles both JSON strings and pre-decoded arrays
    return $this->processData($response);
}

Intersection Types (&) require a value to implement multiple types:

public function executeTransaction(
    Transactable & Loggable $transaction
): void {
    // Object must implement both interfaces
    $transaction->execute();
    $transaction->log();
}

Union types are great for API handling (mentioned in job requirements), while intersection types ensure objects meet multiple interface requirements, supporting robust domain modeling.

Constructor Property Promotion reduces boilerplate code by combining property declaration and constructor parameter assignment:

// Before
class ApiClient {
    private string $apiKey;
    private string $endpoint;
    
    public function __construct(string $apiKey, string $endpoint) {
        $this->apiKey = $apiKey;
        $this->endpoint = $endpoint;
    }
}

// After
class ApiClient {
    public function __construct(
        private string $apiKey,
        private string $endpoint
    ) {}
}

Limitations:

1. Can't use with complex property initialization
2. All properties must use promotion or none
3. Can't combine with default property values outside constructor

This feature aligns with MeritStory's focus on efficient, well-structured code.

Strict Types:

• Enabled via declare(strict_types=1)
• No type coercion allowed
• Throws TypeError on type mismatch
• Perfect for APIs and critical business logic

Weak Types:

• PHP's default behavior
• Allows type coercion
• More flexible but less predictable
• Suitable for simple data handling

For MeritStory's projects, strict typing would be preferred for:

1. RESTful APIs (mentioned in requirements)
2. Financial calculations
3. Healthcare data processing This ensures maximum reliability and maintainability.

JIT (Just-In-Time) compilation converts PHP opcodes into machine code at runtime:

Benefits most in:

1. CPU-intensive operations
2. Long-running processes
3. Mathematical computations
4. Data processing algorithms

Less effective for:

1. Web requests (typical RESTful APIs)
2. I/O-bound operations
3. Database-heavy operations

For MeritStory's work, JIT would be most beneficial in:

• Healthcare data analysis
• Complex financial calculations
• Batch processing tasks

Note: OpCache should be configured first before considering JIT for optimization.

Named arguments allow specifying parameter names when calling functions:

public function createApiClient(
    string $endpoint,
    string $apiKey,
    ?int $timeout = 30,
    bool $verify = true
) {}

// Using named arguments
$client = createApiClient(
    apiKey: $key,
    verify: false,
    endpoint: $url
    // timeout uses default
);

Advantages:

1. Improved readability
2. Skip optional parameters
3. Order-independent
4. Self-documenting code
5. Easier maintenance

This feature is particularly valuable for MeritStory's focus on maintainable, quality code and team collaboration.

Attributes provide several advantages over doc blocks:

1. Native Language Feature:

// Doc block approach
/** @Route("/api/v1/users", methods={"GET"}) */

// Attribute approach
#[Route('/api/v1/users', methods: ['GET'])]

2. Benefits:

• Compile-time validation
• Type-safe
• IDE support
• Can be accessed via reflection
• Can't become outdated like comments

Perfect for MeritStory's RESTful APIs and testing requirements:

#[ApiResource]
#[Test]
#[Route('/api/v1/merit-points')]
class MeritPointsController
{
    // Controller logic
}

Mocks and stubs are both test doubles, but serve different purposes:

Stubs:

• Replace real objects with simplified implementations
• Return predefined responses
• Used when you need to simulate specific scenarios
• Example: Stubbing an API client to return specific data without making real HTTP calls

Mocks:

• Used to verify behavior and interactions
• Assert that specific methods were called with specific parameters
• Verify the number of times a method was called
• Example: Verifying that a logging service was called exactly once with specific error details

Given MeritStory's focus on quality and test coverage, I would use stubs for external services and mocks for verifying critical business logic interactions.

For external services, I implement test doubles using this approach:

1. Interface-based design:

interface PaymentGatewayInterface {
    public function processPayment(Payment $payment): PaymentResult;
}

2. Create test double using PHPUnit's MockBuilder:

$paymentGateway = $this->getMockBuilder(PaymentGatewayInterface::class)
    ->getMock();

$paymentGateway->expects($this->once())
    ->method('processPayment')
    ->willReturn(new PaymentResult('success'));

3. Use dependency injection to inject the test double:

public function testPaymentProcessing()
{
    $paymentService = new PaymentService($paymentGateway);
    $result = $paymentService->handlePayment($payment);
    $this->assertTrue($result->isSuccessful());
}

This approach aligns with MeritStory's emphasis on well-structured code and thorough testing.

The testing pyramid consists of three layers:

1. Unit Tests (Base - 70%):

public function testOrderCalculation()
{
    $calculator = new PriceCalculator();
    $result = $calculator->calculate($order);
    $this->assertEquals(100.00, $result);
}

2. Integration Tests (Middle - 20%):

public function testOrderRepository()
{
    $repository = new OrderRepository($this->entityManager);
    $order = $repository->findById(1);
    $this->assertInstanceOf(Order::class, $order);
}

3. E2E Tests (Top - 10%):

public function testCompleteOrderFlow()
{
    $response = $this->post('/api/orders', [
        'product_id' => 1,
        'quantity' => 2
    ]);
    $response->assertStatus(201);
}

This structure ensures comprehensive testing while maintaining efficient test execution, supporting MeritStory's commitment to high-quality software delivery.

To maintain test coverage in growing codebases, I implement these strategies:

1. CI/CD Pipeline Requirements:

• Enforce minimum coverage thresholds (typically 80%)
• Block merges if coverage decreases
• Generate coverage reports automatically

2. TDD Approach:

// Write test first
public function testUserRegistration()
{
    $service = new RegistrationService();
    $result = $service->register($userData);
    $this->assertTrue($result->isSuccessful());
}

// Then implement the feature

3. Regular Coverage Analysis:

• Use PHPUnit's coverage reports
• Focus on critical business logic
• Identify uncovered code paths

4. Code Review Practices:

• Require tests for new features
• Review test quality along with code
• Ensure test meaningfulness

This aligns with MeritStory's emphasis on quality work and sustainable development pace.

For testing asynchronous operations, I use these approaches:

1. Queue Testing:

public function testJobDispatch()
{
    Queue::fake();
    
    $service->processOrder($order);
    
    Queue::assertPushed(ProcessOrderJob::class, function ($job) use ($order) {
        return $job->order->id === $order->id;
    });
}

2. Event Testing:

public function testEventDispatch()
{
    Event::fake();
    
    $service->completeOrder($order);
    
    Event::assertDispatched(OrderCompleted::class);
}

3. Async API Testing:

public function testAsyncApiCall()
{
    $promise = $client->sendAsyncRequest($request);
    $response = $promise->wait();
    $this->assertEquals(200, $response->getStatusCode());
}

This approach ensures reliable testing of distributed systems, which is crucial for MeritStory's complex client projects.

For REST API integration testing, I follow this comprehensive approach:

1. Setup Test Environment:

class ApiTestCase extends TestCase
{
    use RefreshDatabase;
    
    protected function setUp(): void
    {
        parent::setUp();
        $this->seed(TestingSeeder::class);
    }
}

2. Test HTTP Methods:

public function testApiEndpoints()
{
    // GET request
    $response = $this->getJson('/api/products');
    $response->assertStatus(200)
             ->assertJsonStructure(['data' => ['*' => ['id', 'name']]]);
             
    // POST request with validation
    $response = $this->postJson('/api/products', $data);
    $response->assertStatus(201)
             ->assertJsonFragment(['name' => $data['name']]);
}

3. Authentication Testing:

public function testProtectedEndpoint()
{
    $this->actingAs($user, 'api');
    $response = $this->getJson('/api/protected-resource');
    $response->assertStatus(200);
}

This approach aligns with MeritStory's requirement for RESTful API experience and quality standards.

For database testing, I implement these practices:

1. Test Database Configuration:

class TestCase extends BaseTestCase
{
    use RefreshDatabase;
    
    protected function setUp(): void
    {
        parent::setUp();
        $this->artisan('migrate');
        $this->seed(TestingSeeder::class);
    }
}

2. Transaction Management:

public function testDatabaseOperation()
{
    $this->beginDatabaseTransaction();
    
    $user = User::factory()->create();
    $this->assertDatabaseHas('users', ['email' => $user->email]);
    
    $this->rollBack();
}

3. Data Factories:

public function testOrderCreation()
{
    $user = User::factory()
        ->has(Order::factory()->count(3))
        ->create();
        
    $this->assertEquals(3, $user->orders->count());
}

This approach ensures reliable database testing while maintaining data integrity, supporting MeritStory's focus on handling relational databases effectively.

In PHP applications, I implement bounded contexts by:

1. Creating separate namespaces for each context:

namespace HealthCare\Scheduling;
namespace FinancialServices\Transactions;

2. Maintaining separate database schemas or table prefixes for each context
3. Implementing Anti-Corruption Layers (ACL) between contexts:

class PaymentContextTranslator
{
    public function translateToFinancialTransaction(
        HealthcareAppointment $appointment
    ): FinancialTransaction {
        // Translation logic
    }
}

4. Using Context Maps to define relationships between bounded contexts
5. Ensuring each context has its own independent domain models

This approach aligns well with MeritStory's focus on healthcare and financial projects, ensuring clear separation of complex domain logic.

Entities and Value Objects are fundamental building blocks in DDD:

Entities:

• Have distinct identity (unique ID)
• Mutable over time
• Tracked through system lifecycle

class Patient
{
    private string $id;
    private string $name;
    private DateTime $dateOfBirth;
    
    public function updateName(string $newName): void
    {
        $this->name = $newName;
    }
}

Value Objects:

• Defined by attributes only
• Immutable
• No identity concept

final class Money
{
    private float $amount;
    private string $currency;
    
    public function add(Money $other): Money
    {
        return new Money($this->amount + $other->amount, $this->currency);
    }
}

This distinction is particularly important when working on financial transactions and healthcare systems, as mentioned in MeritStory's project portfolio.

I handle domain events through:

1. Event definition:

class AppointmentScheduled implements DomainEvent
{
    private Appointment $appointment;
    private DateTime $occurredOn;
}

2. Event dispatching within aggregates:

class Appointment
{
    public function schedule(): void
    {
        // Business logic
        $this->domainEvents[] = new AppointmentScheduled($this);
    }
}

3. Event listeners implementation:

class NotifyPatientWhenAppointmentScheduled
{
    public function handle(AppointmentScheduled $event): void
    {
        // Notification logic
    }
}

4. Event bus/dispatcher configuration using modern PHP frameworks like Laravel or Symfony

This approach ensures loose coupling and maintains a clear audit trail of system changes, which is crucial for healthcare and financial systems that MeritStory develops.

To maintain persistence ignorance, I employ these strategies:

1. Interface-based repositories:

interface PatientRepository
{
    public function findById(string $id): ?Patient;
    public function save(Patient $patient): void;
}

2. Domain models free from persistence logic:

class Patient
{
    private string $id;
    private string $name;
    // No ORM annotations in domain model
    // No persistence-related methods
}

3. Infrastructure layer handling persistence details:

class DoctrinePatientRepository implements PatientRepository
{
    public function save(Patient $patient): void
    {
        $this->entityManager->persist($patient);
        $this->entityManager->flush();
    }
}

4. Use of factories for object creation
5. Separation of persistence concerns through proper layering

This approach aligns with MeritStory's high standards of quality and maintainable code.

I implement aggregate roots with these principles:

1. Define clear boundaries:

class MedicalRecord implements AggregateRoot
{
    private Collection $treatments;
    private Patient $patient;
    
    public function addTreatment(Treatment $treatment): void
    {
        // Enforce invariants
        $this->ensureValidTreatmentAddition($treatment);
        $this->treatments->add($treatment);
    }
}

2. Enforce invariants through methods:

private function ensureValidTreatmentAddition(Treatment $treatment): void
{
    if (!$this->isPatientEligible($treatment)) {
        throw new DomainException('Patient not eligible for treatment');
    }
}

3. Implement transactional consistency
4. Use factories for complex creation logic
5. Expose only valid operations through public methods

This implementation ensures data consistency and business rules integrity, which is crucial for MeritStory's healthcare and financial projects.

I implement the repository pattern following these principles:

1. Define repository interfaces in the domain layer:

interface AccountRepository
{
    public function findById(string $id): ?Account;
    public function save(Account $account): void;
    public function findByCustomer(CustomerId $customerId): Collection;
}

2. Implement concrete repositories in infrastructure:

class DoctrineAccountRepository implements AccountRepository
{
    public function __construct(
        private EntityManagerInterface $em
    ) {}
    
    public function findById(string $id): ?Account
    {
        return $this->em->find(Account::class, $id);
    }
}

3. Use specification pattern for complex queries
4. Implement unit of work pattern when needed
5. Handle transactions at the application service level

This approach provides clean separation of concerns and supports MeritStory's focus on well-structured, maintainable code.

I handle business rules by clearly separating responsibilities:

Domain Services:

class TransferDomainService
{
    public function validateTransfer(
        Account $from, 
        Account $to, 
        Money $amount
    ): void {
        // Pure domain logic
        if (!$from->hasEnoughBalance($amount)) {
            throw new InsufficientFundsException();
        }
    }
}

Application Services:

class TransferApplicationService
{
    public function transfer(
        string $fromId, 
        string $toId, 
        float $amount
    ): void {
        // Orchestration, transaction handling
        $this->transactionManager->begin();
        try {
            $from = $this->accountRepository->findById($fromId);
            $to = $this->accountRepository->findById($toId);
            $this->transferDomainService->validateTransfer($from, $to, $amount);
            // Complete transfer
            $this->transactionManager->commit();
        } catch (Exception $e) {
            $this->transactionManager->rollback();
            throw $e;
        }
    }
}

This separation ensures:

1. Domain services focus on pure business logic
2. Application services handle orchestration
3. Clear responsibility boundaries
4. Easier testing and maintenance

This approach is particularly valuable for MeritStory's complex financial and healthcare projects where business rules clarity is essential.

I implement API versioning using three main approaches, depending on project requirements:

1. URI Versioning (/api/v1/users): Pros:

• Simple to implement
• Explicit and clear for clients
• Easy to route in frameworks like Laravel/Symfony Cons:
• Can lead to code duplication
• Not truly REST-compliant

2. Header Versioning (Accept: application/vnd.company.api+json;version=1): Pros:

• More REST-compliant
• Cleaner URLs
• Better for content negotiation Cons:
• More complex to test
• Less visible/discoverable

3. Query Parameter (?version=1): Pros:

• Simple to implement
• Easy for clients to modify Cons:
• Less professional looking
• Can get mixed with other query parameters

In my experience, for most projects, I prefer URI versioning as it provides the best balance of simplicity and maintainability, especially when working with modern PHP frameworks.

I implement rate limiting using a combination of Redis for storage and middleware for enforcement:

class RateLimitMiddleware
{
    private $redis;
    
    public function handle(Request $request, Closure $next)
    {
        $key = $this->getRateLimitKey($request);
        $limit = 100; // requests
        $window = 3600; // seconds
        
        $current = $this->redis->get($key);
        if ($current > $limit) {
            return response()->json([
                'error' => 'Rate limit exceeded'
            ], 429);
        }
        
        $this->redis->incr($key);
        $this->redis->expire($key, $window);
        
        return $next($request);
    }
}

Key features:

• Uses Redis for distributed rate limiting
• Implements sliding window
• Returns proper HTTP 429 status
• Includes rate limit headers in response
• Configurable by client/endpoint

For APIs, I implement a multi-layer authentication and authorization approach:

Authentication:

1. JWT-based authentication:

class JWTAuthMiddleware
{
    public function handle(Request $request, Closure $next)
    {
        $token = $request->bearerToken();
        if (!$token || !$this->validateToken($token)) {
            return response()->json(['error' => 'Unauthorized'], 401);
        }
        return $next($request);
    }
}

2. OAuth2 for third-party integrations
3. API keys for service-to-service communication

Authorization:

1. Role-based access control (RBAC):

#[RoleRequired('admin')]
public function sensitiveOperation(Request $request)
{
    // Only admins can access
}

2. Policy-based authorization for fine-grained control
3. Resource-based permissions

Security considerations:

• HTTPS only
• Token rotation
• Rate limiting per authentication context
• Audit logging

Given MeritStory's focus on quality and client projects, I use a comprehensive documentation approach:

1. OpenAPI/Swagger Specification:

/**
 * @OA\Get(
 *     path="/api/users",
 *     summary="List users",
 *     @OA\Response(
 *         response=200,
 *         description="Successful operation"
 *     )
 * )
 */

2. Auto-generated documentation from code annotations
3. Postman collections for client testing
4. Markdown files for implementation details

Tools I prefer:

• Swagger UI for interactive documentation
• PHPDoc for code-level documentation
• API Blueprint for design-first approach
• Laravel Scribe for automated documentation

This approach ensures:

• Documentation stays in sync with code
• Easy onboarding for new team members
• Clear communication with clients
• Testable examples

I implement HATEOAS (Hypertext as the Engine of Application State) using a dedicated response transformer:

class UserResource extends JsonResource
{
    public function toArray($request)
    {
        return [
            'id' => $this->id,
            'name' => $this->name,
            '_links' => [
                'self' => [
                    'href' => route('users.show', $this->id)
                ],
                'orders' => [
                    'href' => route('users.orders', $this->id)
                ],
                'update' => [
                    'href' => route('users.update', $this->id),
                    'method' => 'PUT'
                ]
            ]
        ];
    }
}

Key aspects:

• Consistent link structure
• Related resource discovery
• State-dependent actions
• Self-documenting responses
• Framework-agnostic implementation

I implement a structured error handling approach that aligns with REST best practices:

1. Global Exception Handler:

class ApiExceptionHandler extends ExceptionHandler
{
    public function render($request, Throwable $e)
    {
        return response()->json([
            'error' => [
                'code' => $this->getErrorCode($e),
                'message' => $this->getMessage($e),
                'details' => $this->getDetails($e)
            ]
        ], $this->getStatusCode($e));
    }
}

2. Custom Exception Classes:

class BusinessRuleException extends Exception
{
    protected $code = 422;
    protected $message = 'Business rule violation';
}

Key features:

• Consistent error format
• Proper HTTP status codes
• Detailed error messages in development
• Sanitized messages in production
• Error logging and monitoring
• Validation error handling
• Rate limit error handling

This approach ensures:

• Clear error communication
• Debugging capability
• Security considerations
• Client-friendly responses

My approach balances theoretical correctness with practical performance needs:

1. Start with proper normalization (3NF) as the default to:

   • Ensure data integrity
   • Minimize redundancy
   • Facilitate maintenance

2. Consider denormalization when:

   • Read performance is crucial for specific features
   • Join operations become a bottleneck
   • The data is relatively static

For example, in healthcare systems (mentioned in job description), I might denormalize patient summary data for quick access while keeping detailed medical records normalized for accuracy and compliance.

Decision factors:

• Read/write ratio
• Data update frequency
• Query complexity
• Performance requirements

My systematic approach to query optimization:

1. Identify slow queries using:

   • MySQL slow query log
   • EXPLAIN ANALYZE
   • Performance Schema

2. Optimization steps:

   • Proper indexing based on WHERE, JOIN, and ORDER BY clauses
   • Analyze and optimize JOIN operations
   • Consider covering indexes for frequently accessed columns
   • Use EXPLAIN to verify execution plans

3. Advanced techniques:

   • Partitioning for large tables
   • Materialized views for complex calculations
   • Query caching using Redis (particularly useful for financial transactions mentioned in job description)
   • Regular ANALYZE TABLE maintenance

Working in a cross-functional team environment requires a robust migration strategy:

1. Version Control:

   • Each migration in a separate file
   • Meaningful naming convention (timestamp_description)
   • Track migrations in version control (Git)

2. Implementation:

   • Use framework migration tools (Laravel/Symfony)
   • Always include both up() and down() methods
   • Keep migrations atomic and focused

3. Team Coordination:

   • Never modify committed migrations
   • Create new migrations for changes
   • Document complex migrations
   • Use CI/CD pipeline to automate migration testing

4. Safety Measures:

   • Backup before migrations
   • Test migrations in staging environment
   • Use transactions where appropriate

My indexing strategy focuses on optimizing performance while considering maintenance overhead:

1. Primary Considerations:

   • Query patterns and frequency
   • Cardinality of columns
   • Write vs read ratio
   • Storage requirements

2. Index Types:

   • Single-column indexes for high-selectivity fields
   • Composite indexes for multiple-column conditions
   • Covering indexes for frequently accessed data
   • Full-text indexes for text search

3. Monitoring and Maintenance:

   • Regular index usage analysis
   • Remove unused indexes
   • Monitor index fragmentation
   • Periodic ANALYZE TABLE execution

4. Special Cases:

   • Partial indexes for filtered queries
   • Descending indexes for ORDER BY optimization

For distributed systems, I implement a comprehensive transaction management strategy:

1. Consistency Patterns:

   • Two-Phase Commit (2PC) for strict consistency
   • Saga pattern for long-running transactions
   • Eventually consistent approaches where appropriate

2. Implementation:

   • Use framework's transaction management
   • Implement retry mechanisms
   • Handle deadlock scenarios
   • Maintain transaction logs

3. Error Handling:

   • Rollback strategies
   • Compensating transactions
   • Error logging and monitoring
   • Circuit breakers for external services

4. Specific to Financial Transactions (mentioned in job description):

   • Implement idempotency
   • Maintain audit logs
   • Use distributed locking when necessary

My approach to soft deletes balances data retention with system performance:

1. Implementation:

   • Add deleted_at timestamp column
   • Use framework's soft delete functionality
   • Implement global scopes for query filtering
   • Consider cascading soft deletes

2. Advantages:

   • Data recovery capability
   • Audit trail maintenance
   • Compliance with data retention policies
   • Historical analysis capability

3. Challenges and Solutions:

   • Index bloat: Partial indexes for active records
   • Query complexity: Proper indexing on deleted_at
   • Storage growth: Implement archiving strategy
   • Unique constraints: Composite unique indexes including deleted_at

4. Best Practices:

   • Clear documentation of soft delete behavior
   • Consistent implementation across related models
   • Regular cleanup of old soft-deleted records
   • Proper handling in API responses

In alignment with 12 Factor principles, I strictly separate configuration from code by:

1. Storing config in environment variables (ENV vars)
2. Using .env files for local development, but never committing them to version control
3. Maintaining different configs for development, staging, and production environments
4. Using a configuration service for distributed systems
5. Following Laravel/Symfony's config management patterns which already implement these principles
6. Ensuring all configuration is stored in a stateless manner to support cloud deployments

This approach ensures our applications remain portable and maintainable across different environments, which is crucial for cloud deployments mentioned in the job requirements.

For cloud-native applications, I implement logging as follows:

1. Treat logs as event streams
2. Write logs to stdout/stderr instead of managing log files
3. Use structured logging (JSON format) for better parsing
4. Implement different log levels (DEBUG, INFO, WARNING, ERROR, CRITICAL)
5. Include correlation IDs for request tracing
6. Use centralized logging services (like ELK Stack or CloudWatch)
7. Implement context-aware logging

This approach supports the high quality and maintainability standards mentioned in the job description, while ensuring proper debugging capabilities in cloud environments.

For secure secrets management in cloud deployments, I:

1. Never store secrets in version control
2. Use cloud-native secrets management services (AWS Secrets Manager, HashiCorp Vault)
3. Implement encryption at rest for all sensitive data
4. Rotate secrets regularly
5. Use role-based access control (RBAC) for secrets access
6. Maintain separate secrets for different environments
7. Implement secure secret injection into containers

This approach aligns with the security needs of financial transactions and healthcare projects mentioned in the job description.

For scaling stateless services, I implement:

1. Horizontal scaling with load balancers
2. Auto-scaling based on metrics (CPU, memory, request count)
3. Container orchestration using Kubernetes or similar tools
4. Microservices architecture where appropriate
5. Caching strategies using Redis
6. Database connection pooling
7. Implementation of circuit breakers for service resilience

This approach ensures high availability and efficiency, which is crucial for the various client projects mentioned in the job description that run for 3-12 months.

For backing services isolation, I:

1. Treat all backing services as attached resources
2. Use dependency injection for service connections
3. Implement interface-based service abstractions
4. Maintain service-specific connection configurations
5. Use container orchestration for service discovery
6. Implement retry mechanisms and circuit breakers
7. Ensure services can be swapped without code changes

This approach supports the company's emphasis on well-structured, maintainable code and allows for efficient handling of different client projects.

For dependency management in a 12 Factor app, I:

1. Explicitly declare all dependencies in composer.json
2. Use Composer for PHP dependency management
3. Implement strict version constraints
4. Generate and commit composer.lock file
5. Use dependency injection for loose coupling
6. Containerize applications with all dependencies
7. Implement automated dependency updates and security scanning

This aligns with the company's focus on quality work and sustainable development practices, ensuring reliable and maintainable applications.