• Position: Senior Software Engineer
• Interview Time: 2024
• Company Type: Finance
• Company Name: Private

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1. Object-Oriented Programming (OOP) Principles

Question: What are the four basic principles of Object-Oriented Programming?

Answer:
The four core principles of OOP are:

1. Encapsulation: Bundling data and methods that operate on the data within a single unit (class).
2. Abstraction: Hiding the implementation details and exposing only the essential features of an object.
3. Inheritance: A mechanism where one class can inherit properties and methods from another.
4. Polymorphism: Allowing objects to be treated as instances of their parent class, enabling method overriding and dynamic method dispatch.

Question: Why is inheritance important in OOP?

Answer:
Inheritance allows code reuse, making the design more modular and maintainable. It also promotes the concept of hierarchical relationships between classes, enhancing code clarity and reducing redundancy.

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2. Functional Programming (FP) vs OOP

Question: What is the difference between Functional Programming and OOP?

Answer:

• OOP focuses on objects and their interactions. It emphasizes mutability, state, and behavior.
• Functional Programming (FP) focuses on functions, immutability, and avoids changing state. It encourages pure functions and higher-order functions to reduce side effects.

Question: When should you prefer FP over OOP?

Answer:
Choose FP when:

• You need stateless functions with predictable behavior.
• You are working with concurrency and parallelism, as FP’s immutability model simplifies these scenarios.

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3. System Design: Scalability and Reliability

Question: What is scalability, and how do you ensure your system scales effectively?

Answer:
Scalability refers to a system’s ability to handle growth in traffic or data efficiently. To ensure scalability:

• Use load balancing to distribute traffic evenly.
• Implement horizontal scaling (adding more machines) or vertical scaling (upgrading existing machines).
• Use caching to reduce database load and enhance response times.

Question: How do you design a system that is both scalable and reliable?

Answer:

• Decouple components into microservices to isolate failures and scale parts of the system independently.
• Ensure redundancy by having backup systems, data replication, and failover mechanisms.
• Use statelessness to ensure that any instance can handle a request, improving reliability and scalability.

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4. Distributed Systems Design

Question: What are the key challenges in designing a distributed system?

Answer:
The main challenges include:

• Network latency and failures.
• Data consistency (eventual consistency vs. strong consistency).
• Partition tolerance (CAP theorem).
• Load balancing and resource allocation.

Question: How do you ensure consistency in a distributed system?

Answer:
You can ensure consistency using protocols like Two-Phase Commit (2PC), Paxos, or Raft. These protocols ensure that a system reaches a consensus on state changes across distributed nodes.

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5. RESTful API Design

Question: What are the key principles of RESTful API design?

Answer:

• Statelessness: Each request must contain all the information necessary to process it.
• Client-Server Architecture: The client and server operate independently.
• Cacheability: Responses should be explicitly marked as cacheable or non-cacheable to improve performance.
• Uniform Interface: A consistent and predictable way to interact with resources.

Question: How do you design a RESTful API that is both efficient and secure?

Answer:

• Use HTTP methods correctly (GET, POST, PUT, DELETE).
• Implement pagination and rate limiting to prevent overload.
• Ensure authentication and authorization via OAuth or JWT.
• Use HTTPS to secure data in transit.

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6. Load Balancing Techniques

Question: What is load balancing, and why is it important?

Answer:
Load balancing distributes incoming network traffic across multiple servers, ensuring no single server is overwhelmed. This improves availability, fault tolerance, and scalability.

Question: What are the common load balancing algorithms?

Answer:

• Round Robin: Distributes traffic evenly across servers.
• Least Connections: Sends traffic to the server with the least active connections.
• IP Hash: Directs traffic based on the client’s IP address to ensure session persistence.

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7. Event-Driven Architecture

Question: What is event-driven architecture?

Answer:
Event-driven architecture is a design pattern where components of a system communicate through events (messages), allowing for asynchronous processing. This architecture enhances system responsiveness and scalability.

Question: How do you implement an event-driven system?

Answer:

• Use message brokers like Kafka, RabbitMQ, or AWS SNS/SQS to handle event communication.
• Design event consumers to process and respond to events in real time.
• Ensure proper event versioning to handle future changes in the system.

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8. Microservices vs Monolithic Architecture

Question: What are the benefits of microservices over monolithic architecture?

Answer:

• Scalability: Microservices allow for scaling specific parts of the application independently.
• Resilience: Failure in one microservice doesn’t affect others.
• Flexibility: Each microservice can use different technologies suited for specific tasks.

Question: What are the challenges of using microservices?

Answer:

• Complexity: More components to manage and maintain.
• Inter-service communication: Requires careful design of APIs and service discovery.
• Data consistency: Ensuring consistency across distributed services can be tricky.

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9. Designing for High Availability

Question: How do you design a highly available system?

Answer:
To design for high availability:

• Replicate data across multiple servers or regions.
• Implement failover strategies to switch to backup systems if the primary fails.
• Use load balancing to distribute traffic and avoid single points of failure.

Question: What is a disaster recovery plan?

Answer:
A disaster recovery plan outlines steps to recover systems and data after a catastrophic failure. It includes having backup systems, off-site backups, and predefined procedures for restoring service.

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10. Cloud-Native Architecture

Question: What is cloud-native architecture, and why is it popular?

Answer:
Cloud-native architecture involves designing applications to run efficiently on cloud platforms, leveraging scalability, flexibility, and high availability. It is popular because it reduces infrastructure management overhead and enhances agility.

Question: How do you design cloud-native applications?

Answer:

• Use containerization (e.g., Docker) to package applications.
• Employ orchestration tools like Kubernetes for managing containers.
• Leverage cloud services like storage, databases, and compute to reduce the need for managing infrastructure.

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