>Digital-flame

In reactive programming, a data flow is like a pipeline where data travels through a series of transformations and reactions — all done in a declarative, non-blocking, and asynchronous way.

You don’t “call” data; it comes to you. You set up a pipeline and let data flow through it.

Reactive Programming is a programming paradigm focused on asynchronous data streams and the propagation of change. It’s all about reacting to data as it comes in — like events, user interactions, or data updates — and building systems that respond to these changes automatically and efficiently.

Absolutely, Stanley! 💡 Let’s implement a simple, thread-safe, bounded buffer using:

• ✅ ReentrantLock for thread safety
• ✅ Condition variables for blocking and coordination
• ✅ Classic producer-consumer pattern

🎯 Goal

• Block put() when buffer is full
• Block take() when buffer is empty
• Avoid synchronized, use explicit locks and condition signaling

📦 What Is a Bounded Buffer?

A bounded buffer is a fixed-size queue that:

• Allows producers to put() items.
• Allows consumers to take() items.
• Blocks producers if the buffer is full.
• Blocks consumers if the buffer is empty.

✅ Key Features:

• Thread-safe with synchronized
• Uses wait()/notifyAll() for coordination
• Fixed-size circular buffer

✅ Requirements

• Thread-safe: Safe for concurrent calls from multiple threads.
• Non-blocking: No synchronized, no locks.
• Returns: BigInteger values doubling each time → 1, 2, 4, 8, 16, ...

💪 Writing a non-blocking ArrayList is a tricky but fun task — because arrays require index-based coordination, which is much harder to do without locks than a linked structure like a stack.

But let’s take it step by step and aim for a minimal lock-free-ish dynamic array structure — using atomic operations only.

✅ Minimal Blocking Stack Using Semaphore

This stack:

• Uses a Deque to store elements
• Uses a Semaphore to track available elements
• Is thread-safe, but not lock-free (uses internal synchronization)

import java.util.Deque;
import java.util.LinkedList;
import java.util.concurrent.Semaphore;

public class SemaphoreStack<T> {
    private final Deque<T> stack = new LinkedList<>();
    private final Semaphore items = new Semaphore(0); // Tracks how many items are available
    private final Object lock = new Object(); // Guards access to the stack

    public void push(T value) {
        synchronized (lock) {
            stack.push(value);
        }
        items.release(); // Signal: one more item available
    }

    public T pop() throws InterruptedException {
        items.acquire(); // Wait until item is available
        synchronized (lock) {
            return stack.pop();
        }
    }
}

🧪 Example Usage:

public class Main {
    public static void main(String[] args) throws InterruptedException {
        SemaphoreStack<Integer> stack = new SemaphoreStack<>();

        stack.push(1);
        stack.push(2);

        System.out.println(stack.pop()); // 2
        System.out.println(stack.pop()); // 1
    }
}

🔍 How It Works:

• items.acquire() blocks if the stack is empty
• items.release() increases the count (available items)
• synchronized protects the internal stack from race conditions

🧠 Summary

🔥 Let’s write a minimal non-blocking stack using lock-free programming with CAS (Compare-And-Swap) operations, leveraging AtomicReference.

🔄 Controlling the execution order of threads (T1 → T2 → T3) is a classic multithreading problem, and there are several ways to achieve it — depending on your style and needs.

✅ Goal: Run Threads in This Exact Order

T1 prints → T2 prints → T3 prints

✅ 1. Minimize Shared Mutable State

The best way to avoid concurrency issues is not to share data at all.

• Prefer immutable objects
• Use thread-local storage when needed
• Copy-on-write or defensive copying strategies