Full-Stack Developer Interview Questions & Answers

This question provides a comprehensive overview of a full-stack developer’s capabilities. Expect them to show proficiency in five categories of technologies: Front-end, back-end, frameworks, databases, and UI design. A full-stack developer must be familiar with them to perform their job effectively. Here are some examples of technologies that fall into these five categories.

 

Front-End	Back-End	Frameworks	Databases	UI Design
HTML	Java	Spring Boot	MongoDB	Figma
CSS	Python	Django	Oracle	Sketch
JavaScript	Golang	React	Microsoft SQL Server	Axure RP
Next.JS	C++	Angular	PostgreSQL	Maze
Svelte	C#	Vue	Redis	Hotjar

 

Frontend is the interface that the user sees and interacts with through the browser. Backend is everything behind the application: server, databases, and business logic.

The Model-View-Controller (MVC) pattern promotes code organization, maintainability, and testability. MVC separates an application into three interconnected parts: the Model, View, and Controller. 

The Model manages the application’s data and business logic (for example, a database). The View presents the user interface, displaying data from the model and handling user interactions. The Controller acts as an intermediary, receiving user input, processing it with the model, and updating the view.

A RESTful API is a flexible web API that obeys the Representational State Transfer (REST) Architecture. It allows a system to communicate with other systems from a different platform in a stateless manner (the server doesn’t have to save the history of HTTP requests), simplifying the server design and improving scalability.

The answer must cover the necessary files and configurations, how the different services communicate with each other, how to handle data persistence for the database, and how to build and deploy this application for a production environment, including any optimizations.

A junior full-stack developer should create a directory for the project, add a docker-compose.yml file, two Dockerfiles (one for the front-end and one for the back-end), and a .dockerignore file to avoid unnecessary files during containerization.

MERN, MEAN, and MEVN are acronyms. M for MongoDB, E for Express.js, and N for Node.js. R, A, and V refer to the most popular frameworks of JavaScript: React, Angular, and Vue.js.

Use MERN for building dynamic and interactive web applications, with regular data updates and real-time features.

Use MEAN for single-page applications (SPAs) with rich, dynamic user interfaces, real-time data streaming apps, and projects benefiting from a consistent JavaScript environment across front-end and back-end.

Use MEVN for projects that need speed, performance, and a lightweight frontend experience, such as a chat app with the capability to share files.

Clean code is important in full-stack development because it makes web applications’ code easier to read, understand, and maintain. Writing clean code is crucial for efficient collaboration and long-term project health. It reduces the likelihood of bugs, accelerates the development process, and lowers maintenance costs.

Expect your candidate to discuss some clean code principles, such as SOLID, KISS, and DRY.

Test automation ensures the quality and reliability of end-to-end web applications. Development teams can catch bugs earlier, improve efficiency, and deliver new features faster with greater confidence and reliability.

Your candidate will address some of the following possible automated tests for full-stack development:

Frontend (UI) Testing

• Tools: Selenium, Cypress, Playwright, TestCafe, Puppeteer.
• Focus: Verifying user interface interactions, responsiveness, visual integrity, and end-to-end user flows.

Backend (API/Service) Testing

• Tools: Postman, SoapUI, RestAssured, JMeter (for performance).
• Focus: Validating API endpoints, data integrity, business logic, security, and performance under load.

Database Testing

• Tools: SQL scripts, ORM-specific testing frameworks, specialized database testing tools.
• Focus: Ensuring data accuracy, consistency, integrity, and performance of database operations.

Unit Testing

• Tools: Jest, Mocha, Karma (JavaScript), JUnit (Java), PyTest (Python), NUnit (C#).
• Focus: Testing individual components or functions in isolation to ensure they work as expected.

Integration Testing

• Tools: Often integrated within unit testing frameworks or using tools like Postman for API integration.

Focus: Verifying the interactions and data flow between different modules or services.

Your candidate here will design an architecture that prioritizes speed of development and leverages managed services to offload operational overhead. Here is an example of how they might approach the challenge. Other approaches are acceptable; don’t expect them to follow the same answer, but their logic will likely be the same on many points.

 

On the front-end, they will use a standard, well-supported choice for programming language and frameworks (for instance, JavaScript/TypeScript with React). Check how they avoid complexity while dealing with State Management and Real-time Communication.

 

On the back-end, they might choose a Serverless Architecture on a public cloud (or private, if your cloud is robust enough and they know it). Such architecture will be scalable by default, but the costs might be burdensome if the MVP gets many requests. In that case, a Ruby or Java server back-end might be slower to produce and have up-front costs, but it will work wonders if the plan is to build the product over the MVP.

For the database, a NoSQL database would be preferable for scalability and performance, such as DynamoDB or MongoDB. As an MVP, it won’t need cache initially. However, if needed, DynamoDB has DAX, which is a fully managed, in-memory cache.

For real-time collaboration logic, when the frontend sends user actions (e.g., {“type”: “insert”, “position”: 10, “text”: “Hello”}) to the WebSocket, the serverless back AWS Lambda receives and validates it. Then Lambda applies the change to the DynamoDB document, and finally broadcasts the update to all other connected clients for that document using the AWS API Gateway Management API.

 

In summary, expect the full-stack senior to plan the web application end-to-end, considering it as an MVP and an initial plan for further development and scalability if needed.

For an early-stage startup, you should always start with a monolith. The primary goal at this stage is to achieve product-market fit as quickly as possible, and a monolith is the best architecture for this. The overhead of microservices (managing multiple codebases, deployment pipelines, and operational complexity) is a massive distraction that can kill a company.

Your candidate will also explain why the monolith is the best architecture and design a plan to transition the web application from the modular monolithic to a microservices architecture. 

While starting with a monolith is the right move, it’s crucial to build it with modularity in mind from day one. This makes the eventual split much easier. You’ll know it’s time to split the monolith into microservices when it’s clear that there are too many requests, making scalability too expensive or infeasible due to the monolithic architecture. You can also change the architecture when deploying a small bug fix or a single new feature requires redeploying the entire, massive application. This increases the risk of introducing new bugs and can lead to significant downtime or instability.

In a normalized schema, this data would be spread across many tables: orders, line_items, users, support_tickets, etc. To generate the dashboard, developers would run several complex queries with multiple JOIN operations. While accurate, these queries can be slow and place a heavy load on the transactional database, potentially impacting the performance of the core application.

An option would be to denormalize a database schema in a scenario that is read-heavy and requires fast query performance, such as a data warehouse for business intelligence (BI) and reporting. 

For example, create a denormalized summary table, perhaps named daily_sales_metrics. This table would store pre-aggregated data, and an Extract, Transform, Load (ETL) or a similar process would run every night to populate this table. For each day, the table might have columns like date, total_sales, new_users, and support_tickets_opened. The dashboard would then query this single table, making the queries significantly faster and more efficient, as they no longer need to perform resource-intensive joins and aggregations on the fly.

Micro-frontends are an architectural pattern where a single large frontend application is broken down into smaller, independent, and loosely coupled applications. Each one of these sub-applications receives a dedicated team. They can be developed and deployed autonomously using different technologies. The final user-facing application is then composed from these independent “micro-apps” at runtime.

Micro-frontends are best suited for large, complex web applications with multiple teams working on different parts of the product. They’re a powerful solution when the sheer size and complexity of the frontend codebase, also known as a “frontend monolith,” becomes a significant bottleneck for development speed and team autonomy.

To design a scalable, high-performance API for a highly trafficked web application, a likely approach would be on a stateless, cache-friendly architecture that uses a RESTful or GraphQL approach. The key is to minimize server-side processing and leverage distributed systems for speed and resilience.

In this case, your candidate will talk about stateless architecture with a multi-layered cache, asynchronous processing, and database scaling. Pay attention to the candidate’s choice of the API’s versioning, because the way an API is versioned directly impacts its performance. For a highly trafficked application, OAuth 2.0 with JWTs (JSON Web Tokens) is the industry standard for securing APIs.