REST, or Representational State Transfer, is an architectural style for designing networked applications. It relies on stateless, client-server communication, using standard HTTP methods like GET, POST, PUT, and DELETE. In Web API development, REST enables scalable and maintainable APIs by structuring resources as URLs and using JSON or XML for data exchange. It simplifies integration with various clients, such as web browsers or mobile apps, by adhering to uniform interfaces and stateless operations.

API versioning ensures backward compatibility while introducing new features. Common methods include URL versioning (e.g., /api/v1/resource), query parameter versioning (e.g., /api/resource?version=1), and header versioning. I prefer URL versioning for its clarity and ease of use. It allows clients to explicitly specify the version they need, reducing confusion. Proper documentation and deprecation policies are also crucial to guide users during transitions.

Securing a Web API involves multiple layers of protection. Use HTTPS to encrypt data in transit, implement authentication (e.g., OAuth 2.0 or JWT) to verify user identity, and enforce authorization to control access to resources. Validate and sanitize inputs to prevent injection attacks, and employ rate limiting to mitigate abuse. Regularly update dependencies to patch vulnerabilities and conduct security audits to identify and address potential risks.

Optimizing API performance involves reducing latency and improving scalability. Use caching (e.g., Redis) to store frequently accessed data, minimize payload size with compression, and paginate large datasets to reduce response times. Optimize database queries and use asynchronous processing for long-running tasks. Load balancing and horizontal scaling can also distribute traffic efficiently, ensuring high availability and responsiveness.

I use tools like Postman and Swagger for manual testing and debugging, ensuring endpoints behave as expected. For automated testing, I rely on frameworks like Jest, Mocha, or pytest to write unit and integration tests. Load testing tools like JMeter or Gatling help evaluate performance under stress. These tools ensure the API is reliable, secure, and performs well under various conditions.