Coroutine-like Generator: C has no built-in coroutine support like Python or Kotlin. But using static variables and switch macros, we can simulate a "generator". This helps produce one value at a time across function calls. Ideal for stateful iteration without global variables.

Deep Clone using Serialization: Cloning objects with nested fields is hard without deep copy. This trick uses serialization to copy entire object graphs. It's powerful and generic works on any Serializable object. Use it in undo systems, cache snapshots, or state management.

Centroid Decomposition on Trees: Centroid Decomposition helps solve problems on trees involving distance, paths, or subtrees. It breaks the tree into layers based on centroids (nodes which balance the tree). Useful for path queries, color counting, or subtree analysis in O(N log

Implementing Circuit Breaker with Resilience4j: Circuit Breakers help prevent cascading failures in microservices. With Resilience4j, you can automatically trip the circuit after repeated failures. This improves system resilience under high load or backend issues. Spring Boot

Hey.. I always play with these two commands in my GitBash What about you guys🙂?

Spinlock with Atomic Flag: Spinlocks are lightweight locking mechanisms used in multicore CPUs. They avoid context-switching by actively waiting for the lock. C11’s atomic_flag makes them easy and thread-safe to implement. Best for short critical sections to reduce overhead.

Retry Utility with Lambdas: In real systems, operations can fail temporarily (e.g., network). Instead of writing manual retries, wrap them in a clean utility. This code uses Java lambdas to retry any function easily. Great for resilience in distributed systems or flaky I/O.

Persistent Segment Tree: It lets you maintain multiple versions of a segment tree (immutably) using pointers. You can query historical states of an array in O(log N) time and space. Used in k-th order statistics on subarrays, or undo-based problems. Powerful for range counting

Using Async with @Async and Executor in Spring Boot: Asynchronous execution improves responsiveness for background tasks. Spring’s @Async lets you run methods on separate threads seamlessly. You can configure custom Executor for performance tuning. Common in email sending, file

JWT Authentication with Spring Security: JWT-based security is stateless and ideal for REST APIs. Spring Security allows token parsing, validation, and role-based access. You intercept the request with a filter and authenticate it. Secure, scalable, and avoids session storage on

Fast Walsh-Hadamard Transform (FWT) for XOR Convolution: FWT is like FFT but for XOR convolutions. It’s used in problems involving subset sums, XOR bases, or probability on XOR masks. Computes convolutions in O(N log N) for bitmask-like DP or signal analysis. Efficient for

Java Sandbox using SecurityManager: Want to restrict what a block of code can access (like files)? Use Java's SecurityManager to sandbox dangerous operations. This allows safe execution of plugins or user scripts. Not commonly used, but powerful for advanced control.

I have explained how Retry Handle Temporary Failures Automatically in Spring Boot: Here's the link: youtu.be/aMohkd_VeTE?si…

I have explained how @Retry Handle Temporary Failures Automatically in Spring Boot: Here's the link: youtube.com/shorts/aMohkd_…

Bit Fields: In C, sometimes we don’t need a full int or char to store simple flags like on/off, true/false, or small range values. Bit fields let you allocate exact bits (like 1-bit, 4-bit, etc.) for each field in a struct, packing more information into less space. This is super

Bit-Level Manipulations with Bitfields and Unions: -> Struct members with specified bit widths for compact storage of flags or settings, ideal for hardware registers or protocols. -> Enable multiple views of the same memory, allowing bitfields and raw integers to coexist for

Java Functional Programming with Streams and Lambdas: Streams handle filtering, sorting, and reducing, while lambdas simplify function definitions. In Spring, they power reactive APIs; in competitions, they optimize data tasks. The example below shows a Spring REST endpoint

Spring WebFlux with Reactive Streams for Scalable APIs: Spring WebFlux leverages reactive programming with Java Streams and Project Reactor to build non-blocking, scalable APIs. Reactive Streams process asynchronous data flows efficiently, ideal for high-throughput applications

Here's the link: youtu.be/Mc7G0hMWgwo?si… I have explained clearly about types and usage of database. Also which database suits ur application.