TypeScript Developer Interview Questions

From a non-technical perspective, this question might sound like a mere syntax question. However, this TypeScript developer interview question tests both syntax knowledge and understanding of design choices and architectural implications in a large project.

In TypeScript, both the interface and type keywords (with the type alias) define the shape (structure) of objects. However, they have important differences, particularly in how they can be extended and how the compiler handles them.

The choice between interface and type in a large project is a matter of convention, maintainability, and extensibility.

When to Choose an Interface

An interface is often the default choice for defining the shape of objects in a large application.

• Data Models and APIs: Use an interface for objects that represent data (e.g., user models, API responses, configuration objects).
• Class Implementation: Use an interface to define Class Contracts (using the implements keyword), ensuring that the class has a specific set of properties and methods.
• Extensibility and Standards (Libraries/Plugins): Declaration merging is crucial when creating libraries or when you need code consumers to extend typing without changing the source code. For example, extending types from third-party libraries (such as adding a property to an Express request object).

When to Choose a Type (Type Alias)

A type should be used when you need features that the interface doesn’t support.

• Non-Object Types: Always use type to create unions (type Status = ‘active’ | ‘inactive’), tuples (type RGB = [number, number, number]), or aliases for primitive types (type UserID = string).
• Type Mapping and Modification: Use type when working with Conditional Types and Mapped Types (advanced features) to create new types based on others.
• Type Composition: Use the intersection operator (&) to combine types declaratively (type NewProps = OldProps & ExtraProps;).

A good guideline for managers and senior developers is this Golden Rule:

“Use interface to define the form of an object or class contract, and use type for anything else (unions, tuples, primitive types, or advanced Mapped Types).”

This rule simplifies the decision, standardizes the codebase, and ensures that the declaration merging feature is reserved for cases where it is actually needed (such as in libraries or to extend types).

The ability to use Mapped Types and Conditional Types to create this separation in a clean and generic way is what demonstrates senior architectural knowledge. Some TypeScript developer interview questions must assess a candidate’s understanding of the Separation of Concerns (SoC). A candidate must know not only advanced features, but also their applicability for maintainability and architectural problems.

One of the most common and impactful scenarios is State Management or the creation of Dynamic Forms in large-scale front-end applications (such as React, Angular, or Vue).

1. The Problem: Type Duplication in Forms (Mapped Types)

In a large application, it’s common to have a main data model (User, Product, etc.). However, the form that edits it needs a version of that model:

1. The main model may have keys that shouldn’t be editable (id, createdAt).
2. All form keys may need to be optional (for a “Partial Edit” form).
3. All keys may need a special type to manage their state (for example, adding an isValid: boolean to each field).

The problem is having to rewrite the form’s typing from the main model.

2. The Robust Solution: Mapped Types

We use a Mapped Type to automatically generate the form’s typing from the base type, ensuring that the form’s typing is always synchronized with the data model.

3. Advanced Usage: Conditional Types

What if we want a field’s value to not contain the undefined type (even if the original property is optional), unless it’s a union type? We use a Conditional Type to refine the type of each key.

When answering, the candidate should highlight the following points:

This answer demonstrates not only syntax knowledge but also the ability to apply it to create clean, generic abstractions. This is at the heart of senior software development.

The file tsconfig.json is not just a configuration file, but as the backbone of the architecture and code quality of a large project. tsconfig.json is the tool that allows us to delegate error checking to the TypeScript compiler, instead of finding them at runtime (production).

Strict configurations mean that the most common JavaScript bugs (like null or undefined references) are detected and fixed before the code is even deployed. It saves time and money on post-release fixes.

In other words, tsconfig.json is the written policy of TypeScript’s error detection, errors that were hard to pinpoint in JavaScript.

In large teams, it ensures that all developers follow the same typing rules and project structure. This facilitates collaboration, code review, and onboarding of new members, as the compiler acts as a consistent quality inspector.

For projects with multiple modules or internal libraries, tsconfig.json (along with references) clearly defines the boundaries and dependencies between project components (monorepos). It makes compilation faster (compiling only what has changed) and the code structure more organized and easier to navigate.

In short, tsconfig.json ensures the software’s quality, costs, and maintainability.

The following options are good choices for the tsconfig.json’s configuration.

By presenting an answer that demonstrates scalability, build performance, and code quality, a TypeScript developer shows their worth.

A decorator is a function that is prefixed with the @ symbol and placed immediately before the definition you want to modify. It’s a TypeScript developer interview question that assesses knowledge of TypeScript metaprogramming. The importance lies in creating clean, declarative code and efficient integration with frameworks.

Using Decorators in advanced scenarios often involves manipulating metadata to automate tasks. With Dependency Injection (DI), a developer no longer needs to manage the creation and passing of services, which drastically simplifies object construction logic and facilitates unit testing.

The usefulness of this TypeScript developer interview question lies in ensuring that the software will be fast, reliable, and built with tools that minimize errors in real-time. It tests a candidate’s capability in handling scalability, reliability, and selecting technologies beyond daily coding.

The challenge is to build a system that can send messages (notifications) to many users immediately and reliably.

The basic architecture for real-time notifications requires a persistent connection, which is the opposite of normal HTTP requests (which open and close quickly). Below is an example of components that must be used in such an architecture. The key technology for each component of the application is a suggestion, not the “correct” answer.

TypeScript is essential here because it enforces a strict data contract between the backend and frontend.

Both Notification Format and Safe Refactoring are implemented through a Single Interface. This prevents bugs by eliminating mismatched field errors during compilation.

Furthermore, it enables safe refactoring, as updates to the structure require global changes via TypeScript, preventing breakages and saving testing time.

In short, TypeScript’s type safety transforms the notification format from an error-prone “verbal agreement” into a compiler-enforced “legal contract.”

Choosing between a monolithic architecture and microservices is the most important decision for a growing e-commerce platform. It defines how code is organized, how teams work, and, most importantly, how the platform handles increased demand (scalability).

In a monolithic model, all application code (product catalog, payments, users, checkout) is built and deployed as a single large unit. It’s easier and faster to design and deploy, but it doesn’t scale as much as microservices.

Microservices architecture divides an application into a set of small, independent services (e.g., Product Service, Payment Service, Shopping Cart Service). Each can be developed, deployed, and scaled separately. If one fails, it doesn’t affect the other services. However, it’s more expensive (each service requires a specialized team) and harder to maintain and coordinate due to the increasing complexity. See, microservices communicate through APIs (contracts). The biggest risk is that one service changes its response and breaks the consuming service. 

TypeScript is a crucial enabler to mitigate this risk. It allows you to define these APIs (the types of data sent and received) explicitly, using interfaces or types. If a contract changes, TypeScript forces a compilation error in the consuming service, preventing runtime errors and reducing debugging time caused by network communication.

The transition to microservices is inevitable for global scalability and feature development speed for a growing e-commerce business. TypeScript acts as a safety net for this transition, ensuring that the complexity of communication between services doesn’t turn into costly production bugs.

SOLID is an acronym for five software design principles that, when followed, make code more understandable, flexible, and maintainable. They are the foundation for good code quality.

TypeScript, with its emphasis on interfaces and strong typing, is an ideal tool for enforcing SOLID.

1. S – Single Responsibility Principle (SRP)

A class or module should have only one reason to change.

Practical Example (Anti-Pattern): A Report class that is responsible for:

1) Calculating the data,

2) Formatting it to PDF, 

and 3) Sending it by email. 

If the email sending method changes, the entire class must be modified and retested.

Business Value: Reduces the risk of introducing bugs. If you change the PDF formatting, you don’t affect the calculation logic.

2. O – Open/Closed Principle (OCP)

Software entities (classes, modules) should be open for extension, but closed for modification.

Practical Example: You have a function that calculates shipping. The rule is: never change the existing calculation function. Instead, add a new one.

Business Value: Agility in adding features. Adding a new shipping rule (International Shipping) does not require touching the already tested and working checkout code.

3. L – Liskov Substitution Principle (LSP)

Objects of a superclass should be substitutable with objects of their subclasses without breaking the application.

Practical Example: If a Duck can be replaced by a RubberDuck without breaking the code that uses it, the principle is respected. The error is creating a subclass that throws unexpected exceptions (e.g., a RubberDuck tries to fly and fails).

Business Value: Reliability. Ensures that abstract code (e.g., a payment module that accepts any BankAccount) will always work, regardless of the specific account type being used.

4. I – Interface Segregation Principle (ISP)

Clients should not be forced to depend on interfaces they do not use. It is better to have many small, specific interfaces than a single large, generic one.

Practical Example: Instead of having a SuperEmployee interface with 20 methods (like pay, hire, fire, archive), we create small interfaces.

Business Value: Loose coupling and clarity. Classes depend only on the minimum necessary. This makes the code easier to read and reduces the risk of a “side effect” when modifying a class.

5. D – Dependency Inversion Principle (DIP)

High-level modules should not depend on low-level modules. Both should depend on abstractions (interfaces).

Practical Example: The Checkout (high-level module) should not depend directly on a MySQLDatabase class (low-level module). It should depend on an OrderRepository interface.

Business Value: Flexibility and Testability. If the business decides to change from MongoDB to PostgreSQL, only the low-level class needs to be swapped. The OrderProcessor code doesn’t change because it depends on the IOrderRepository interface. This also facilitates unit testing (by mocking the interface).

Both REST (Representational State Transfer) and GraphQL are architectural styles for API communication between the client (your web/mobile application, written in TypeScript) and the server. The main difference lies in who determines the structure of the data returned.

With REST APIs, a TypeScript client needs to define an interface for each endpoint response. However, if the server changes a field name (userName to fullName), the interface on the client silently breaks in production. The developer must manually keep the types synchronized.

Pairing TypeScript with the GraphQL ecosystem brings more benefits, with tools like Apollo Client or Relay, which enable Automatic Type Generation. The developer writes the GraphQL query, and a tool automatically generates the exact TypeScript types based on the request.

The integration between TypeScript and GraphQL is natively typed. If the query changes or the GraphQL server changes its schema, the client’s TypeScript code fails to compile, alerting the developer immediately to the error. It anticipates an entire class of bugs before deployment and dramatically speeds up development.

When to Use Each

The decision should be based on data complexity and performance needs. For CRUDs, Third-Party Resources, and Robust Cache on the Client side, REST is enough. REST is good enough for most cases.

However, we use GraphQL with TypeScript when performance and type safety between frontend and backend are critical.

In short, answering this question assures the recruiter that the candidate not only knows how to code but also knows how to build a defensible, high-quality system that will be sustainable as the business grows.

A senior TypeScript developer doesn’t just write working code; they write code that can be proven to work and continues to work after future changes.

The main advantage of TypeScript in testing is its type safety. TypeScript acts as the first level of testing (the compilation test). The compiler catches common errors (typos, functions called with incorrect arguments) before any unit testing begins. Plus, TypeScript enables type mock objects, ensuring that the simulated data is identical to the real object being tested.

Before talking about the tools, we will talk about the test pyramid model. The Testing Pyramid is an architectural concept that guides test efforts: many rapid tests at the base and slower, thorough tests at the top.

The choice of tools demonstrates the candidate’s familiarity with the modern JavaScript/TypeScript ecosystem.

Jest/Vitest (Unit and Integration Tests)

Jest has been the industry standard for years (meta-owned by Facebook), known for its excellent test runner, easy mocking, and snapshot support.

Vitest is the modern choice, lighter, faster (especially for large projects), and integrates seamlessly with Vite- and Esbuild-based projects.

The choice between Jest and Vitest demonstrates the candidate’s ability to evaluate trade-offs between legacy and performance.

Playwright (End-to-End Tests)

Playwright (from Microsoft) is the cutting-edge E2E tool. It offers better performance than older alternatives and can be tested in multiple browsers (Chrome, Firefox, Safari) with a single configuration. It also supports advanced features like tracing (recording videos and screenshots of the crash).

Mocking is the practice of replacing real dependencies of a component (such as API calls, database access, or third-party modules) with simulated versions (Mocks) during unit testing.

It brings many benefits. Test Isolation, for example. Mocking ensures that a unit test only fails if the tested code fails, not because an external service is down. It makes test feedback reliable and instantaneous. 

Another benefit is execution speed. Mocks are simple in-memory objects that avoid network latency and disk/database access. 

Finally, mocking enables the testability of edge cases, simulating difficult-to-reproduce scenarios (e.g., a network error, a user without permission). It ensures that the application behaves correctly in failure situations.

The main decision for a senior Typescript developer is how to manage these Mocks: manually and transparently or using the abstraction of a library. A senior, balanced approach combines the best of both worlds, leveraging TypeScript to mitigate the risks of manual mocking and libraries for efficiency.

• Use Library Mocking (Jest/Vitest) to mock modules and trace calls (spies), as it’s fast and efficient.
• Use Manual Mocking (Typed with TypeScript) to mock complex domain objects (repository classes, API clients) using the implements keyword in the mock class.

By doing this, the developer ensures test runner speed and contract safety (which is the biggest benefit of TypeScript), preventing mocks from deviating from the actual behavior of the system.

This is the pinnacle of the interview for a senior developer. Not pure technical knowledge (syntax or principles) but rather leadership ability, a quality engineering mindset, and real business impact.

Business owners and recruiters managers: this is the proof-of-value question. It shows whether the candidate is a change agent who actively improves the project, rather than just executing tasks.

Recruiter, ask yourself:

1. Can the candidate identify a pain point in the project (e.g., slow tests, inconsistent code, many production bugs)?
2. Did the candidate propose and implement the solution, often convincing the team of the value and dedicating time to it (beyond normal features)?
3. Can the candidate quantify the impact (e.g., bug reduction by X%, build speed improved by Y seconds), linking the technical improvement to the business benefit?

This question is a test of advanced TypeScript proficiency. It assesses whether the senior candidate understands the type not just as an annotation tool, but as a design and programming logic tool capable of enforcing business rules and eliminating bugs before the code is even executed.

A developer who uses the type system as a test is building software with zero bugs in a category of errors. The result? Safer code, less debugging time, and greater confidence in the system.

One of the best examples your candidate might bring is using Discriminated Unions to model data states that change over time (such as the state of an API request or the state of an Order).

A TypeScript developer’s ability to handle technical disagreements is a direct indicator of their effectiveness in a collaborative, high-pressure environment.

A good code review philosophy is based on the principle that time spent reviewing should maximize value and minimize friction. Code review has two main goals: ensuring system quality and ensuring developer growth.

In short, a senior uses Code Review as a lever to ensure that code is robust and that developers learn to think architecturally and securely.

When reviewing any peer’s code, the integrity of the system is the top priority.

The key for a good TypeScript developer is to adapt the focus of the review to the junior’s experience, treating a junior’s review as a mentoring session. The goal is to teach and develop good habits, prioritizing learning over immediate perfection.

While reviewing a colleague’s code, the goal is to challenge the architecture and performance, assuming the code base is functionally correct.

This TypeScript developer interview question doesn’t assess the candidate’s coding skills, but rather their non-managerial leadership skills and their role as a knowledge multiplier. It’s vital for a senior, as a senior’s impact isn’t measured solely by the code they write, but by how much they raise the technical level of the entire team.

• Accelerates Onboarding: Is this candidate able to quickly integrate and make new talent productive?
• Reduces Dependency: Avoids being the sole point of expertise (“bottleneck”) in critical areas.
• Creates a Culture of Quality: Helps establish standards of excellence and best practices (such as TypeScript and SOLID) across the team.

A senior developer’s most important role in fostering team growth is to be the Guardian and Promoter of Engineering Standards. This goes beyond providing answers; it’s about explaining the reasons behind architectural decisions and delegating context.

This final question assesses the senior candidate’s mentoring and communication skills, focusing on their ability to simplify complexity. A senior isn’t just someone who solves the toughest problems, but also someone who empowers others to solve them.

For business owners and hiring managers, this question is useful in assessing the effectiveness of mentoring. A good mentor accelerates talent development, ensuring that investment in junior developers quickly pays off.

For the sake of an example, let’s talk about Generics in TypeScript. The concept of Generics is often one of the biggest obstacles for new TypeScript developers. The explanation should be based on real-world analogies and practical examples, rather than technical jargon.

We can explain Generics as cargo containers for a ship. Imagine you’re building a function (the ship) whose job is to move data.

Without Generics (No Defined Type), it’s like having a container (the function) where you can put anything (any). You move the container, but when you open it, you have no idea what’s inside (cars, bananas, coal). This is unsafe.

With Generics (<T>), it’s like having a universal container, but you tag it before putting anything inside. Now you know what is inside!

The letter <T> is just a placeholder for a type that will be defined later. You’re telling TypeScript, ‘I don’t know what type it will be, but I guarantee that the type going in is the same type going out.’ The T (for Type) is the tag that ensures consistency.

When explaining Generics, the senior should focus on how it solves an engineering problem. It avoids having to write the same function (identityNumber, identityString) for each type. It also avoids using “any” and, consequently, ensures autocompletion and safe refactoring in client code.

The senior should encourage the junior to see Generics as the tool that allows TypeScript to be flexible and reusable, maintaining strong typing where it matters most. The goal is for the junior to understand that Generics is the key to writing libraries and utility functions that work for any data type.