Best coding practice with Designing High-Performance, Optimized code

In the world of software development, it becomes critical to ensure that your code is not only functional but also efficient, maintainable, and scalable. Designing high-performance, optimized code is essential for delivering applications that respond quickly, use fewer resources, and are easier to debug and enhance over time. 

This guide highlights key principles and patterns that help developers write clean, fast, and optimized code—covering everything from algorithmic thinking and resource management to design patterns and performance monitoring. 

We will cover: 

• How to design clean and scalable REST APIs 

• Techniques to write optimized service methods  

  
  

Best Practices for Designing RESTful APIs 

• The most common and recommended case for RESTful API URLs is: kebab-case (also called dash-case): all lowercase with words separated by hyphens (-). 

Valid: GET/user-info/{userId}, PUT/admin-details, 

Not Valid: GET/getUserInfo, PUT/AdminDetails  

• Always use meaningful concise API name. Don’t make the API name unnecessarily lengthy and ambiguous. 

Appropriate: GET/user-info/{userId}, PUT/admin-details, GET/user/all 

Inappropriate: GET/get-user-info, PUT/updateAdminDetails, GET/getAllUsers  

• Always use path variable when value is essential to identify a specific resource. 

  
  

Example: GET /users/{userId} , DELETE /products/123, PUT /orders/789  

• Request Param should be used when the value is optional and used for filtering, sorting, searching, pagination etc. Example: GET /users? role=admin, GET /products? category=shoes&page=2&limit=10, GET /search?param=laptop  

• If you want to insert new data or update existing data, you should send the request in a structured format using the Request Body 

  
  

N.B. Request body can only be used with POST, PUT and PATCH. GET and DELETE does not support that.  

• If you need to pass a POJO in GET API in Spring Boot application and Feign Client is being used for inter-service communications you can use @SpringQueryMap to pass the POJO class. 

• Status codes matter: Return the right status code: 200 OK, 201 Created, 400 Bad Request, 404 Not Found, 500 Internal Server Error 

Code Optimization  

• Instead of writing whole code in a single function, isolate common features in a separate function and call it from the parent function. 

• Use Functional Programming Methods like map, filter that provides more power to the developer and make your code more expressible.  

• Avoid Repetitive Computation by storing results of expensive calculations if they are to be reused (memorization or caching).  

  
  

  

  
  

• Batch DOM updates or use virtual DOM techniques (e.g., React) to reduce performance overhead.  

• In scenarios where there is a need to display large data sets, use Lazy Loading and Pagination only load or render what is visible to users — this improves performance.  

• Using JPA Specification instead of standard Hibernate methods like findByField, findByStatusAndType, etc., is a powerful and flexible way to build dynamic queries in Spring Data JPA. This is especially helpful when you have optional filters or need to compose complex queries. 

  
  

Case Studies 

Case Study 1 – Lazy Loading & Pagination 

A patient dashboard loaded all patients into the browser grid on page load. 

• First load took over 20 seconds. 

• UI became unresponsive. 

Solution: 

• Added server-side pagination with limit and offset query params. 

• Implemented lazy loading in the front end to fetch next pages only when needed. 

Result: 

• First page loads in under 1 second. 

• Browser memory usage reduced by over 80%. 

Case Study 2 – Functional Programming for Cleaner Code 

Legacy code for processing orders was full of nested for loops: 

for (let i=0; i<orders.length; i++) { 

  if (orders[i].status === 'PENDING') { 

    let price = calculatePrice(orders[i]); 

    // …   } } 

Solution: Rewrote using map and filter: 

orders.filter(order => order.status === 'PENDING').map(order => ({ ...order, price: calculatePrice(order) })); 

Result: 

• Code size reduced by 30%. 

• Much easier for new developers to comprehend and maintain.  

  
  

Case Study 3 – Database Query Optimization in E-Commerce 

An hospital ERP’s patient search was taking 2–3 seconds per request because each query joined 6–7 tables with no indexing. 

Solution: 

• Added composite indexes on patient_id. 

• Rewrote queries to use EXISTS instead of nested IN. 

Result: 

Query time reduced from 2.7s → 150ms, leading to faster page loads and higher user retention. 

Conclusion  

Code optimization is not just about speed — it is about writing efficient, clean, and scalable code that performs well and is easy to maintain over time. It should be guided by actual performance metrics, not assumptions. 

Ultimately, high-performance code is a balance of efficiency and clarity. Following best practices ensures your applications are not just fast but also robust and easy to evolve with future requirements.