Java Method Overloading by Parameter Order

#Day11⚡ Parallel Streams — easy parallelism in Java Want parallelism with minimal code? 👉 Just switch from stream() → parallelStream() list.parallelStream() .map(x -> x * 2) .forEach(System.out::println); 💡 Behind the scenes: Uses ForkJoinPool Splits data into chunks Executes in parallel ⚠️ But be careful: Avoid shared mutable state Not ideal for IO tasks 👉 Great for CPU-heavy data processing #Java #Multithreading #ParallelStream #Concurrency #JavaDeveloper #ForkJoinPool #InterviewPreparation #LearningInPublic

🚀 Fork/Join Framework (Java) The Fork/Join framework is designed for parallelizing recursive tasks. It uses a work-stealing algorithm to efficiently distribute tasks among available threads. The framework consists of the `ForkJoinPool` and `RecursiveTask` (for tasks that return a result) or `RecursiveAction` (for tasks that don't return a result) classes. Fork/Join is particularly well-suited for divide-and-conquer algorithms, such as sorting and searching large datasets, where tasks can be recursively broken down into smaller subtasks. #Java #JavaDev #OOP #Backend #professional #career #development

🚀 Day 11 – The Volatile Keyword in Java (Visibility Matters) While exploring multithreading, I came across the "volatile" keyword—simple, but very important. class SharedData { volatile boolean flag = false; } 👉 So what does "volatile" actually do? ✔ It ensures that changes made by one thread are immediately visible to other threads Without "volatile": - Threads may use cached values - Updates might not be seen → leading to unexpected behavior --- 💡 Important insight: "volatile" solves visibility issues, not atomicity 👉 This means: - It works well for simple flags (true/false) - But NOT for operations like "count++" (still unsafe) --- ⚠️ When to use? ✔ Status flags ✔ Configuration variables shared across threads 💡 Real takeaway: In multithreading, it’s not just about execution—visibility of data is equally critical #Java #BackendDevelopment #Multithreading #Concurrency #LearningInPublic

Day 65 — LeetCode Progress (Java) Problem: Find All Numbers Disappeared in an Array Required: Given an array of size n containing numbers in the range [1, n], return all the numbers that are missing from the array. Idea: Compare the expected range [1…n] with the actual elements to identify missing values. Approach: Initialize a set containing all numbers from 1 to n. Traverse the array: Remove each element from the set The remaining elements in the set are the missing numbers. Time Complexity: O(n) Space Complexity: O(n) #LeetCode #DSA #Java #HashSet #Arrays #Algorithms #CodingJourney #100DaysOfCode

Every Java developer uses String. Almost no one understands this 👇 String is immutable. But it’s NOT just a rule you memorize. It’s a design decision that affects: Security. Performance. Memory. Here’s why it actually matters: 🔒 Security Imagine if database credentials could change after creation… dangerous, right? ⚡ Memory (String Pool) "hello" is stored once. Multiple variables → same object That’s only possible because it’s immutable. 🚀 Performance Strings are used as HashMap keys Since they don’t change: Hashcode is cached → faster lookups So next time you hear “String is immutable”… Remember: It’s not a limitation. It’s an optimization. #Java #SoftwareEngineering #Programming #BackendDevelopment #LearningJourney

🚀 Are you already using Parallel Streams in Java? Parallel Streams can be a great tool for improving performance in collection operations by taking advantage of multiple CPU cores to process data in parallel. With a simple change: list.stream() to: list.parallelStream() or: list.stream().parallel() it’s possible to execute operations like filter, map, and reduce simultaneously. But be careful: parallelizing doesn’t always mean speeding things up. ⚠️ Some important points before using it: ✅ It’s worth it when: * There is a large amount of data; * Operations are CPU-intensive; * Tasks are independent and side-effect free. ❌ It may make things worse when: * The collection is small; * There are I/O operations (database, API calls, files); * There is synchronization or shared state; * Processing order matters. Also, Parallel Streams use ForkJoinPool.commonPool() by default, which may cause contention with other tasks in the application. 💡 Rule of thumb: measure before you optimize. Benchmarking with tools like JMH can help avoid decisions based on guesswork. When used correctly, Parallel Streams can be a powerful way to gain performance with minimal code changes. #Java #Performance #Backend #SoftwareDevelopment #Programming

📖 New Post: Java Memory Model Demystified: Stack vs. Heap Where do your variables live? We explain the Stack, the Heap, and the Garbage Collector in simple terms. #java #jvm #memorymanagement

Day 33/100 — Threads & Multithreading ⚡ Java can do multiple things at the same time using threads. Thread lifecycle: NEW → RUNNABLE → RUNNING → WAITING → TERMINATED 2 ways to create threads: // Method 1: extend Thread class MyThread extends Thread {   public void run() { println("Running!"); } } new MyThread().start(); // NOT run()! // Method 2: Runnable lambda (preferred!) Thread t = new Thread(() -> println("Lambda thread!")); t.start(); Most important rule: ALWAYS call start() — NOT run()! → run() = normal method call (same thread) → start() = creates new thread and calls run() 3 things to remember: → Prefer Runnable over extending Thread → start() not run() → Multiple threads = race conditions possible! 🎯 Challenge: Create 3 threads that each print their name 5 times. Observe the interleaved output! #Java #Threads #Multithreading #CoreJava #100DaysOfJava #100DaysOfCode

Day 36/100 – Working with ArrayList in Java 📚 Today I practiced using ArrayList in Java, a dynamic array that allows flexible storage and manipulation of data. Unlike normal arrays, ArrayList can grow and shrink dynamically, making it very useful in real-world applications. Key learnings: • Adding elements using add() • Storing multiple values dynamically • Finding size using size() • Easier and more flexible than traditional arrays Understanding collections like ArrayList is important for handling data efficiently in Java. Building strong fundamentals step by step. 🚀 #100DaysOfCode #Java #ArrayList #DataStructures #CodingJourney #LearningInPublic

Day 7 of #100DaysOfCode — Java is getting interesting ☕ Today I explored the Java Collections Framework. Before this, I was using arrays for everything. But arrays have one limitation — fixed size. 👉 What if we need to add more data later? That’s where Collections come in. 🔹 Key Learnings: ArrayList grows dynamically — no size worries Easy operations: add(), remove(), get(), size() More flexible than arrays 🔹 Iterator (Game changer) A clean way to loop through collections: hasNext() → checks next element next() → returns next element remove() → safely removes element 🔹 Concept that clicked today: Iterable → Collection → List → ArrayList This small hierarchy made everything much clearer. ⚡ Array vs ArrayList Array → fixed size ArrayList → dynamic size Array → stores primitives ArrayList → stores objects Still exploring: Set, Map, Queue next 🔥 Consistency is the only plan. Showing up every day 💪 If you’re also learning Java or working with Collections — let’s connect 🤝 #Java #Collections #ArrayList #100DaysOfCode #JavaDeveloper #LearningInPublic