73 Full Stack Developer Interview Questions and Answers PDF 2025

Full-stack developers are versatile professionals who bridge the gap between front-end and back-end development, possessing expertise in both client-side and server-side technologies to build complete web applications from start to finish.

They handle everything from user interface design and user experience to database architecture, server management, and API integration, making them invaluable assets in today’s fast-paced development environment.

As companies increasingly seek developers who can work across the entire technology stack, the competition for full-stack positions has intensified significantly, making comprehensive interview preparation essential for success.

This comprehensive guide features Full Stack Developer Interview Questions and Answers for both fresher and experienced full-stack developers. Beyond general full-stack concepts, we have also included dedicated sections with specialized questions for Java, .NET, and Python full stack interview questins with answers.

Full Stack Developer Interview Questions and Answers for Freshers

Que 1. What are the core technologies you should know as a Full Stack Developer?

A Full Stack Developer should be proficient in:

Technology Area	Examples
Frontend	HTML, CSS, JavaScript, React, Angular, Vue.js
Backend	Node.js, Express, Django, Spring Boot, .NET
Database	MySQL, PostgreSQL, MongoDB, Redis
Version Control	Git, GitHub
Other Skills	REST APIs, basic cloud deployment (AWS, Azure), DevOps basics

Que 2. What is the difference between SQL and NoSQL databases?

• SQL Databases: Structured, use tables, rows, and columns. Examples: MySQL, PostgreSQL.
• NoSQL Databases: Unstructured or semi-structured, store data as documents, key-value pairs, or graphs. Examples: MongoDB, Cassandra.
  Use SQL for complex queries and relationships, NoSQL for flexibility and scalability.

Que 3. What is REST API and why is it important?

REST API (Representational State Transfer) is an architectural style that uses HTTP methods (GET, POST, PUT, DELETE) to interact with resources.

• It makes communication between frontend and backend easier.
• It is stateless, scalable, and supports multiple data formats (JSON, XML).

Que 4. Explain the difference between GET and POST methods in HTTP.

• GET: Used to fetch data, parameters are sent in the URL, and it’s idempotent.
• POST: Used to send data to the server, parameters are sent in the request body, and it’s not idempotent.

Example:

GET /users?id=1
POST /users

Que 5. What is the difference between synchronous and asynchronous programming in JavaScript?

• Synchronous: Tasks run one after another, blocking the main thread.
• Asynchronous: Tasks run independently, and the result is handled later (via callbacks, promises, or async/await).
  Example: fetch() is asynchronous, alert() is synchronous.

Que 6. What are the differences between cookies, localStorage, and sessionStorage?

• Cookies: Stored on the client and sent with every request; size ~4KB.
• localStorage: Stores data permanently until manually cleared; size ~5MB.
• sessionStorage: Stores data only for the session; size ~5MB.

Que 7. What is CORS and why do we need it?

CORS (Cross-Origin Resource Sharing) allows browsers to access resources from a different origin (domain). Without CORS, browsers block requests for security reasons. Backend servers must send specific headers like:

Access-Control-Allow-Origin: *

Que 8. Explain MVC architecture in web applications.

• Model: Handles data and business logic
• View: Handles UI and presentation
• Controller: Handles user requests and connects the Model and View
  This separation improves scalability and maintainability.

Que 9. What are some ways to improve website performance?

• Minify and bundle CSS/JS
• Use CDN for static assets
• Implement caching (browser, server, CDN)
• Optimize images (WebP, compression)
• Lazy load heavy components
• Use pagination for large datasets

Que 10. What is JWT (JSON Web Token) and how is it used for authentication?

JWT is a token-based authentication mechanism containing three parts: Header, Payload, and Signature. It is sent in the request headers (usually Authorization) to verify the user identity without storing session data on the server.

Que 11. What are the differences between SSR and CSR?

Feature	SSR (Server-Side Rendering)	CSR (Client-Side Rendering)
Rendering Location	Server	Client (browser)
Initial Load Speed	Faster	Slower
SEO Friendliness	Better (search engines can easily index content)	Poorer (requires extra steps for SEO)
Use Case Example	Next.js	React SPA
Best For	Static or content-heavy websites needing SEO	Dynamic and interactive web applications

Que 12. How do you handle form validation on frontend and backend?

• Frontend: Validate input using HTML5 attributes or JavaScript.
• Backend: Always validate again for security using libraries like Joi (Node.js) or built-in frameworks validation.

Que 13. What are the advantages of using a framework like Express or Django for backend?

• Faster development with built-in features (routing, middleware, ORM)
• Security best practices (XSS, CSRF protection)
• Large community and plugins support (required, pattern)
• Better structure for scalable apps

Que 14. How does a browser render a webpage?

1. Browser parses HTML and builds DOM
2. Parses CSS and builds CSSOM
3. Combines DOM and CSSOM into a Render Tree
4. Performs layout and painting to display the page
   JavaScript execution can block this process if not optimized.

Que 15. What is the difference between PUT and PATCH in HTTP methods?

• PUT: Replaces the entire resource with new data.
• PATCH: Updates only the specified fields.

Example:

PUT /user/1   --> Send entire user object
PATCH /user/1 --> Send only the field(s) to update

Que 16. How would you secure a web application?

• Use HTTPS everywhere
• Validate and sanitize user input (to prevent SQL Injection/XSS)
• Implement authentication and authorization properly
• Use security headers (Content-Security-Policy, X-Frame-Options)
• Keep dependencies updated
• Rate-limit APIs to prevent abuse

Que 17. What are WebSockets and when would you use them?

WebSockets provide a full-duplex, persistent connection between the client and server. They are ideal for real-time applications like chat apps, gaming, or stock tickers. Unlike HTTP, it doesn’t need to make a request for every update.

Que 18. Explain how you would design a simple login system.

1. Frontend: Create a login form with email & password
2. Backend: Verify user credentials against the database
3. Security: Hash passwords using bcrypt
4. Token: Generate a JWT and send it to the client
5. Storage: Store token in httpOnly cookie or localStorage
6. Authorization: Validate the token on protected routes

Que 19. How would you handle scalability for a growing web application?

• Use load balancers
• Implement horizontal scaling (multiple servers)
• Use database replication and sharding
• Cache frequently accessed data using Redis or Memcached
• Implement microservices architecture when needed

Que 20. What steps would you take to debug a Full Stack application issue?

• Frontend: Check browser console logs, inspect network requests
• Backend: Check server logs, use debugging tools (like console.log , breakpoints)
• Database: Test queries directly, check for errors or slow queries
• End-to-end: Use tools like Postman or automated tests to isolate the issue
  Document the issue and fix incrementally to avoid breaking other parts of the system.

Also Check: Web Development Interview Questions

Full Stack Developer Interview Questions and Answers for Experienced

Que 21. How do you design a scalable architecture for a high-traffic web application?

For high-traffic applications, you should:

• Use load balancers to distribute traffic across multiple servers.
• Implement horizontal scaling using containers (Docker, Kubernetes).
• Cache data at different levels (CDN, reverse proxy, in-memory stores like Redis).
• Optimize database with replication, partitioning, and connection pooling.
• Use asynchronous processing (message queues like RabbitMQ or Kafka).

Que 22. What are microservices and how do they differ from monolithic architecture?

• Microservices: Independent, loosely coupled services communicating over APIs.
• Monolithic: Single codebase handling all modules tightly coupled together.
  Microservices provide better scalability, independent deployments, and fault isolation. Monoliths are simpler but harder to scale and maintain.

Que 23. How do you handle state management in a distributed system?

• Use stateless services whenever possible.
• Persist state in distributed caches (Redis, Memcached) or databases.
• For sessions, use shared stores (Redis, DynamoDB) instead of in-memory sessions.
• Apply sticky sessions only if necessary.

Que 24. Explain database indexing and its impact on performance.

Indexes improve query performance by creating a fast lookup path. However, they slow down write operations (INSERT, UPDATE, DELETE) and consume storage.
Example:

CREATE INDEX idx_users_email ON users(email);

Always analyze query patterns and avoid over-indexing.

Que 25. How do you handle API versioning in a live application?

• Use versioned endpoints like /api/v1/ and /api/v2/.
• Maintain backward compatibility and deprecate older versions gradually.
• Use feature flags for experimental features.
• Document all versions using OpenAPI/Swagger.

Que 26. What is the difference between optimistic and pessimistic locking?

• Optimistic Locking: Assumes no conflicts; validates version numbers before committing.
• Pessimistic Locking: Locks data at read time to prevent conflicts.
  Optimistic locking is better for high-read/low-write systems; pessimistic is suitable for high-contention environments.

Que 27. How would you secure sensitive data at rest and in transit?

• In Transit: Use HTTPS/TLS for all communications.
• At Rest: Use AES encryption for database fields or files.
• Apply key management policies (e.g., AWS KMS, HashiCorp Vault).
• Hash sensitive data like passwords using bcrypt or Argon2.

Que 28. How do you improve the performance of a slow API endpoint?

1. Profile queries and use proper indexing.
2. Implement caching at DB, application, and response levels.
3. Use pagination instead of fetching large datasets.
4. Break heavy tasks into asynchronous jobs.
5. Reduce payload size (Gzip, Brotli, or GraphQL partial queries).

Que 29. How do you handle deployment and rollback strategies in production?

• Blue-Green Deployment: Keep two environments and switch traffic after testing.
• Canary Deployment: Release to a small user segment before full rollout.
• Keep previous builds ready for instant rollback.
• Automate deployment pipelines with CI/CD tools (Jenkins, GitHub Actions).

Que 30. What are some advanced caching strategies you have used?

• Write-through cache: Write to cache and DB simultaneously.
• Write-back cache: Write to cache first, then DB asynchronously.
• Cache invalidation policies: TTL (Time-To-Live), versioning, and manual invalidation.
• Layered caching with CDN + in-memory + database-level caching.

Que 31. How do you implement rate limiting and throttling in APIs?

• Use middleware like NGINX rate limit, API Gateway policies, or libraries like express-rate-limit.
• Strategies: Token bucket, leaky bucket, fixed window, sliding window.
• Return 429 Too Many Requests when limit is reached.

Que 32. How do you design a database schema for scalability?

• Normalize for consistency, then denormalize for performance when necessary.
• Use partitioning/sharding for large datasets.
• Avoid heavy joins by designing for read patterns.
• Choose appropriate data types and constraints.

Que 33. How do you debug memory leaks in a Node.js or Java application?

• Use tools like Chrome DevTools, heap snapshots, Node’s –inspect, or jmap (Java).
• Look for objects retained in memory unexpectedly.
• Monitor GC (Garbage Collection) metrics.
• Fix by removing unused listeners, closing DB connections, and clearing caches.

Que 34. How do you handle distributed transactions in microservices?

• Use the Saga pattern (choreography or orchestration).
• Use eventual consistency with retries and compensating actions.
• Avoid 2-phase commits in high-scale systems due to complexity.

Que 35. Explain the difference between horizontal and vertical scaling.

• Horizontal scaling: Add more servers/instances to handle load.
• Vertical scaling: Increase hardware capacity (CPU/RAM) on a single server.
  Horizontal scaling is more fault-tolerant and cost-effective in the long run.

Que 36. How do you design a logging and monitoring system for full-stack applications?

• Centralize logs with tools like ELK Stack, Graylog, or Splunk.
• Implement structured logging (JSON format).
• Use metrics and dashboards with Prometheus, Grafana, or Datadog.
• Add alerting based on thresholds and anomalies.

Que 37. How do you optimize frontend performance for large applications?

• Code splitting and lazy loading using Webpack or Vite.
• Minify and tree-shake unused JS/CSS.
• Use image optimization (WebP, responsive images).
• Reduce re-renders in React/Vue by using memoization.

Que 38. How do you design a CI/CD pipeline for full-stack applications?

• Automate builds, tests, and deployments.
• Use tools like Jenkins, GitHub Actions, or GitLab CI.
• Include security scans and code quality checks.
• Support multiple environments (dev, staging, production).

Que 39. How do you ensure high availability and fault tolerance in production?

• Deploy across multiple availability zones or regions.
• Use load balancers and health checks.
• Implement circuit breakers and retries in APIs.
• Ensure databases have replicas and automatic failover.

Que 40. How would you architect a real-time collaborative application (like Google Docs)?

• Use WebSockets or WebRTC for real-time communication.
• Maintain an operational transform (OT) or CRDT-based data structure for conflict resolution.
• Persist updates in a distributed database.
• Ensure scalability with message brokers like Kafka for broadcasting changes.

Also Check: Front end Developer and Back end Developer interview Questions Guides

Java Full Stack Developer Interview Questions and Answers

Que 41. What are some common Java frameworks used in full stack development and why?

• Spring Boot: Simplifies backend development with auto-configuration and embedded servers.
• Hibernate/JPA: Provides ORM for database access.
• Spring Security: Handles authentication and authorization.
• Thymeleaf: Used for server-side rendering.
• Frontend frameworks: Angular, React, or Vue.js commonly used for UI.
  These frameworks speed up development, provide ready-to-use modules, and improve maintainability.

Que 42. How does Spring Boot simplify backend development compared to traditional Spring?

Spring Boot eliminates boilerplate configurations by using auto-configuration and opinionated defaults. It includes an embedded Tomcat/Jetty server, enabling applications to run as standalone JARs. It also provides an Actuator module for monitoring and health checks, making it faster to build production-ready services.

Que 43. What are RESTful APIs in Spring Boot and how do you implement them?

RESTful APIs follow the REST architecture, using HTTP methods to interact with resources. Example:

@RestController
@RequestMapping("/api/users")
public class UserController {
    @GetMapping("/{id}")
    public User getUser(@PathVariable Long id) {
        return userService.findById(id);
    }
}

This exposes /api/users/{id} as an API endpoint using GET method.

Que 44. How do you manage state in a Java full stack application?

• Use stateless services as much as possible.
• For sessions, use Spring Session backed by Redis instead of in-memory sessions.
• Store persistent user data in databases and use JWT tokens for authentication.
• Client-side state can be handled using Redux (React) or NgRx (Angular).

Que 45. How do you integrate the frontend (React/Angular) with a Spring Boot backend?

• Expose REST APIs or GraphQL endpoints from Spring Boot.
• Use HttpClient (Angular) or fetch/axios (React) to call APIs.
• Enable CORS in backend:

@CrossOrigin(origins = "*")
@RestController
public class ApiController { }

• Use JWT or OAuth2 for secure communication between frontend and backend.

Que 46. How do you handle database transactions in a Java full stack application?

Spring provides the @Transactional annotation to manage transactions:

@Transactional
public void transferFunds(Long fromId, Long toId, BigDecimal amount) {
    accountRepository.debit(fromId, amount);
    accountRepository.credit(toId, amount);
}

This ensures atomicity, rollback on failure, and consistency across multiple operations.

Que 47. What are the best practices for exception handling in Spring Boot applications?

• Use @ControllerAdvice with @ExceptionHandler to centralize error handling.
• Return meaningful error messages with proper HTTP status codes.
• Log exceptions with stack traces using SLF4J/Logback.
  Example:

@ControllerAdvice
public class GlobalExceptionHandler {
    @ExceptionHandler(Exception.class)
    public ResponseEntity<String> handleException(Exception ex) {
        return ResponseEntity.status(HttpStatus.INTERNAL_SERVER_ERROR).body(ex.getMessage());
    }
}

Que 48. How do you secure a Java full stack application?

• Use Spring Security for authentication and authorization.
• Implement JWT or OAuth2 token-based authentication.
• Use HTTPS and configure security headers.
• Validate and sanitize all user inputs to prevent XSS/SQL Injection.
• Encrypt sensitive data using strong encryption algorithms like AES.

Que 49. How do you implement asynchronous processing in Spring Boot?

• Use @Async annotation with @EnableAsync for async methods.
• Use CompletableFuture or message queues like RabbitMQ/Kafka for background processing.
  Example:

@Async
public CompletableFuture<String> sendEmail(String to) {
    // email sending logic
    return CompletableFuture.completedFuture("Email Sent");
}

Que 50. How do you design a Java full stack application for scalability?

• Use microservices with Spring Cloud instead of monoliths.
• Implement horizontal scaling with load balancers.
• Use caching (Redis, Ehcache) to reduce DB load.
• Optimize database with connection pooling (HikariCP).
• Use container orchestration (Docker, Kubernetes) for distributed deployment.

Que 51. How would you debug a performance bottleneck in a Java full stack application?

1. Backend: Use profiling tools (VisualVM, YourKit) to find slow methods or memory leaks.
2. Database: Analyze slow queries with EXPLAIN and add indexes where needed.
3. Frontend: Use Chrome DevTools to monitor rendering and network latency.
4. Enable detailed logs and use distributed tracing (Zipkin, Jaeger) for microservices.
5. Stress test the application using JMeter or Gatling to reproduce issues.

Also Check: Java interview Questions and Answers

.Net Full Stack Developer Interview Questions and Answers

Que 52. What are the common technologies used in a .NET full stack application?

A typical .NET full stack application includes:

• Backend: ASP.NET Core (Web API, MVC), Entity Framework Core for ORM.
• Frontend: Angular, React, or Blazor.
• Database: SQL Server, PostgreSQL, or NoSQL databases like MongoDB.
• Authentication: IdentityServer, JWT, OAuth2.
• DevOps: Azure DevOps, Docker, Kubernetes for CI/CD and containerization.

Que 53. How do you create a REST API using ASP.NET Core?

In ASP.NET Core, create a controller decorated with [ApiController] and define endpoints:

[ApiController]
[Route("api/[controller]")]
public class UsersController : ControllerBase {
    [HttpGet("{id}")]
    public IActionResult GetUser(int id) {
        var user = userService.GetById(id);
        return Ok(user);
    }
}

Use dependency injection for services and register them in Startup.cs or Program.cs.

Que 54. How does dependency injection work in ASP.NET Core?

ASP.NET Core has built-in dependency injection (DI). You register services in the container and inject them where needed:

// Registration
services.AddScoped<IUserService, UserService>();

// Usage
public class UsersController {
    private readonly IUserService _service;
    public UsersController(IUserService service) { _service = service; }
}

This improves testability and decouples components.

Que 55. How do you integrate Angular or React frontend with an ASP.NET Core backend?

• Use SPA templates (dotnet new angular or dotnet new react).
• Serve static files from wwwroot or host frontend separately.
• Enable CORS in backend:

app.UseCors(builder => builder.AllowAnyOrigin().AllowAnyMethod().AllowAnyHeader());

• Communicate via REST APIs using HttpClient (Angular) or fetch/axios (React).

Que 56. How do you manage database transactions in Entity Framework Core?

Use DbContext and transaction APIs:

using var transaction = await context.Database.BeginTransactionAsync();
try {
    context.Users.Add(user);
    await context.SaveChangesAsync();
    await transaction.CommitAsync();
} catch {
    await transaction.RollbackAsync();
}

SaveChanges() automatically wraps operations in a transaction if none exists.

Que 57. How do you implement authentication and authorization in ASP.NET Core?

• Use ASP.NET Core Identity for user management.
• Implement JWT token-based authentication for APIs.
• Configure policies and roles:

services.AddAuthorization(options => {
    options.AddPolicy("AdminOnly", policy => policy.RequireRole("Admin"));
});

• Secure endpoints using [Authorize] attribute.

Que 58. How do you handle exceptions globally in a .NET full stack application?

Use middleware or UseExceptionHandler in Startup.cs:

app.UseExceptionHandler(appBuilder => {
    appBuilder.Run(async context => {
        context.Response.StatusCode = 500;
        await context.Response.WriteAsync("An error occurred.");
    });
});

For structured error responses, create a custom middleware and log using ILogger.

Que 59. How do you improve performance in a .NET full stack application?

• Enable response caching and use CDN for static files.
• Optimize database with indexes and compiled queries.
• Use asynchronous programming (async/await) for I/O operations.
• Implement caching with MemoryCache or distributed caches like Redis.
• Reduce payload size by using compression middleware.

Que 60. How do you implement real-time communication in .NET applications?

Use SignalR for real-time communication:

public class ChatHub : Hub {
    public async Task SendMessage(string user, string message) {
        await Clients.All.SendAsync("ReceiveMessage", user, message);
    }
}

On the frontend, connect using JavaScript or Angular/React SignalR clients to receive updates instantly.

Que 61. How would you design a .NET full stack application for scalability?

• Use microservices with ASP.NET Core and Docker/Kubernetes.
• Implement API Gateway (Ocelot) for routing and security.
• Use horizontal scaling and load balancers (Azure Load Balancer, NGINX).
• Apply distributed caching (Redis) and database sharding.
• Store configuration and secrets in Azure Key Vault or AWS Secrets Manager.

Que 61. How would you debug and diagnose performance issues in a .NET full stack application?

1. Backend: Use Application Insights or dotnet-trace for profiling.
2. Database: Analyze slow queries with SQL Server Profiler or Explain.
3. Frontend: Use browser DevTools to monitor rendering, network latency, and API calls.
4. Implement structured logging with Serilog or NLog and correlate logs with request IDs.
5. Set up distributed tracing using OpenTelemetry or Azure Monitor for microservices.

Also Check: C# Interview Questions and Answers

python Full Stack Developer Interview Questions and Answers

Que 63. What are the common frameworks used for Python full stack development?

• Backend: Django, Flask, FastAPI.
• Frontend: React, Angular, Vue.js, or Django’s built-in templates.
• Database: PostgreSQL, MySQL, SQLite, MongoDB.
• Tools: Celery for background tasks, Redis for caching, Docker for containerization.

Que 64. How does Django differ from Flask in full stack development?

• Django: Full-featured, includes ORM, authentication, admin panel, and follows “batteries-included” approach.
• Flask: Lightweight, minimalistic, flexible with external libraries.
  Django is better for large-scale apps, while Flask suits smaller, microservice-based applications.

Que 65. How do you create REST APIs in Django or Flask?

In Django, use Django REST Framework (DRF):

from rest_framework.viewsets import ModelViewSet
class UserViewSet(ModelViewSet):
    queryset = User.objects.all()
    serializer_class = UserSerializer

In Flask, use Flask-RESTful:

from flask_restful import Resource
class UserResource(Resource):
    def get(self, user_id):
        return {"user": user_id}

Que 66. How do you integrate React or Angular frontend with a Django or Flask backend?

• Serve the frontend as static files or host it separately.
• Enable CORS using django-cors-headers or Flask-CORS.
• Consume backend APIs using axios (React) or HttpClient (Angular).
• For production, use a reverse proxy like NGINX to handle both frontend and backend.

Que 67. How do you handle authentication and authorization in Python full stack apps?

• Use Django’s built-in authentication or Flask-Login for session-based auth.
• For token-based auth, use JWT (djangorestframework-simplejwt or PyJWT).
• Implement OAuth2 with libraries like Authlib or django-allauth.
• Secure endpoints using decorators like @login_required or DRF’s Is Authenticated permission class.

Que 68. How do you manage database migrations in Django and Flask?

• Django: Uses built-in makemigrations and migrate commands.
• Flask: Uses Flask-Migrate (based on Alembic). Example:

flask db migrate -m "initial"
flask db upgrade
Migrations ensure database schema is version-controlled and consistent.

Que 69. How do you implement background tasks in Python full stack applications?

Use Celery with a message broker (Redis, RabbitMQ):

from celery import shared_task
@shared_task
def send_email_task(user_id):
    # logic to send email

Schedule periodic tasks with Celery beat or APScheduler.

Que 70. How do you secure Python full stack applications?

• Always use HTTPS (TLS).
• Validate and sanitize user input to prevent XSS/SQL Injection.
• Use CSRF tokens (csrf_protect in Django).
• Set secure cookies (HttpOnly, Secure, SameSite) .
• Keep dependencies updated and use bandit or safety to scan for vulnerabilities.

Que 71. How would you design a Python full stack application for scalability?

• Break into microservices using FastAPI or Flask for lightweight APIs.
• Use horizontal scaling with Docker + Kubernetes.
• Add caching layers (Redis, Memcached).
• Use database sharding and replication.
• Implement load balancing (NGINX, AWS ALB) and asynchronous message queues.

Que 72. How do you implement real-time features in Python full stack apps?

• Use Django Channels or Flask-SocketIO for WebSocket support.
• Example with Flask-SocketIO:

from flask_socketio import SocketIO
socketio = SocketIO(app)
@socketio.on('message')
def handle_message(msg):
    send(msg, broadcast=True)

• Use Redis as a message broker for scalable pub/sub events.

Que 73. How would you debug performance issues in a Python full stack application?

1. Backend: Use profiling tools like cProfile, py-spy, or Django Debug Toolbar.
2. Database: Analyze slow queries using EXPLAIN and optimize indexes.
3. Frontend: Check network latency and rendering issues using Chrome DevTools.
4. Use APM tools (New Relic, Sentry, Elastic APM) for distributed tracing.
5. Stress test with Locust or JMeter to reproduce performance bottlenecks.

Also Check: Python Interview Questions and Answers

Full Stack Developer Interview Questions PDF

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FAQs: Full Stack Developer Interview Questions