Day 94/100 – #100DaysOfCode 🚀 | #Java #DynamicProgramming #UnboundedKnapsack ✅ Problem Solved: Coin Change II (LeetCode 518) 🧩 Problem Summary: Given an integer amount and an array of coin denominations, return the number of combinations that make up the amount. Each coin can be used unlimited times, and the order of coins does not matter. 💡 Approach Used: ✔ Used Dynamic Programming (1D DP) ✔ This is a classic Unbounded Knapsack problem Steps: Initialize dp[0] = 1 (one way to make amount 0) For each coin: Iterate from coin to amount Update dp[i] += dp[i - coin] This ensures combinations are counted, not permutations ⚙ Time Complexity: O(N × amount) 📦 Space Complexity: O(amount) (where N = number of coins) ✨ Takeaway: The order of loops in DP matters! Iterating coins first avoids counting duplicate permutations and keeps combinations unique. #Java #LeetCode #DynamicProgramming #UnboundedKnapsack #100DaysOfCode #CodingChallenge
Java Dynamic Programming Solution for Coin Change II
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Day 92/100 – #100DaysOfCode 🚀 | #Java #DynamicProgramming #Strings ✅ Problem Solved: Longest Palindromic Subsequence (LeetCode) 🧩 Problem Summary: Given a string, find the length of the longest subsequence that is also a palindrome. (A subsequence does not need to be contiguous.) 💡 Approach Used: ✔ Used Dynamic Programming (2D DP) ✔ Define dp[i][j] as the length of the longest palindromic subsequence in substring s[i…j] Logic: If s[i] == s[j] → dp[i][j] = 2 + dp[i+1][j-1] Else → dp[i][j] = max(dp[i+1][j], dp[i][j-1]) Fill the table bottom-up by increasing substring length ⚙ Time Complexity: O(N²) 📦 Space Complexity: O(N²) ✨ Takeaway: Problems involving subsequences often hint toward DP. Breaking the string into overlapping subproblems makes complex patterns manageable. #Java #LeetCode #DynamicProgramming #Strings #100DaysOfCode #CodingChallenge
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#Java 💎 #Diamond #Operator (<>) ✨ 🔹 Introduced in Java 7 🔹 Used with Generics 🔹 Removes duplicate generic type 🔹 Compiler infers the data type automatically 🔹 Reduces boilerplate code 🔹 Improves code readability 🔹 Works with Collections & custom generic classes 🔹 Compile-time feature (no runtime cost) 📌 Example List<String> list = new ArrayList<>(); Map<Integer, String> map = new HashMap<>(); ⚠️ Limitation ❌ Not allowed with anonymous inner classes (Java 7/8)
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📘 Core #Java Deep Dive – Foundations That Matter Core #Java provides the fundamental building blocks that form the backbone of real-world Java applications. These concepts define runtime behavior, memory management, and essential #OOP principles Key Concepts: ✅ Object & Class Class ✅ System Class ✅ Strings (String, StringBuffer, StringBuilder) ✅ Arrays ✅ Boxing & Unboxing ✅ Varargs ✅ format() & printf() ✅ Inheritance & Access Modifiers ✅ Method Overriding ✅ Constructor Chaining ✅ Type Casting ✅ instanceof 💡 Understanding these concepts is essential for writing robust, maintainable, and efficient #Javaprograms. 📂 Notes with code examples: 👉 https://lnkd.in/geV_JueJ #CoreJava #JavaProgramming #SoftwareEngineering #OOP #BackendDevelopment #DeveloperCommunity #Programming #TechLearning #JavaDeveloper #Coding
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Ever wonder why Java is the backbone of enterprise tech? It's all thanks to the 'Janitor' we call Garbage Collection. 🧹 Instead of developers manually managing memory, Java's GC automatically identifies 'dead' objects and clears them out. It’s the difference between cleaning up after your own party or having a professional crew do it for you while you keep hosting. #Java #Programming #TechSimplified #SoftwareEngineering"#SpringBoot
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Ready to take a trip down memory lane—and build something cool in the process? This tutorial walks you through how to recreate the classic Snake game in Java, complete with logic, rendering, and controls. Sample code included. #Java #GameDev #CodingProjects #ProgrammingBasics #RheinwerkComputingBlog Read here: https://hubs.la/Q03-ngrv0
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This Java nested loop prints an increasing number pattern, but more importantly, it strengthened my understanding of how logic grows step by step. 💡 Every pattern teaches something new: ✔ Control of nested loops ✔ Relationship between rows & columns ✔ Building problem-solving mindset Simple code today, stronger developer tomorrow 💻🔥 👉 Consistency > Complexity #Java #NestedLoops #PatternProgramming #LogicBuilding #JavaDeveloper #CodingJourney #LearnByDoing #ProgrammingBasics
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Day 29/100 ✅ LeetCode 138: Copy List with Random Pointer Solved this problem by creating a deep copy of a linked list where each node contains an additional random pointer. The approach ensures that both next and random pointers are copied correctly without modifying the original list. Key steps involved: Create copied nodes Link copied nodes with original nodes Assign random pointers efficiently Separate the original and cloned lists This problem helped me strengthen my understanding of linked list manipulation and pointer mapping. Solution:-https://lnkd.in/gD9TWWsg #LeetCode #LeetCode138 #CopyListWithRandomPointer #LinkedList #DSA #Java #ProblemSolving #CodingPractice #DeepCopy #DataStructures #Day29
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Day 97/100 – #100DaysOfCode 🚀 | #Java #Strings #Logic ✅ Problem Solved: Longest Uncommon Subsequence I (LeetCode) 🧩 Problem Summary: Given two strings, find the length of the longest uncommon subsequence — a subsequence that appears in one string but not in the other. 💡 Approach Used: ✔ Observational / logical approach ✔ If both strings are equal, no uncommon subsequence exists ✔ If they are different, the longer string itself is the answer Why it works: A string is always a subsequence of itself If strings differ, the longer one cannot be a subsequence of the shorter ⚙ Time Complexity: O(1) 📦 Space Complexity: O(1) ✨ Takeaway: Some problems look like DP but are solved with pure logic. Always check for simple observations before overengineering. #Java #LeetCode #Strings #Logic #100DaysOfCode #CodingChallenge
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Java 21 Virtual Threads change how we design backend services. In this hands-on tutorial, I build a pixel-art image processing service with Quarkus and Java 21, using Virtual Threads for the entire request lifecycle. Blocking image I/O and CPU-heavy pixel math. No reactive stack. No worker pools. Just clean, synchronous Java. If you are evaluating where Virtual Threads actually fit in production systems, this is a practical example. Read the full article: https://lnkd.in/dcMZENC4 #Java #Java21 #Quarkus #VirtualThreads #SoftwareArchitecture #BackendEngineering
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HashMap🛠️ Vs ConcurrentHashMap 🏗️ 1. HashMap 🛠️ Thread-Safety: Not thread-safe. If multiple threads access it simultaneously, it can lead to race conditions or the infamous "Infinite Loop" during resizing. Locking: No locking mechanism. Nulls: Allows one null key and multiple null values. Performance: Fastest in a single-threaded environment. 2. ConcurrentHashMap 🏗️ Thread-Safety: Fully thread-safe. Designed specifically for high-concurrency. Locking Strategy: It doesn't lock the whole map. It uses Bucket-Level Locking (or Compare-And-Swap in newer Java versions). This means Thread A can write to Bucket 1 while Thread B writes to Bucket 2 simultaneously! Nulls: Does NOT allow null keys or values (to avoid ambiguity in multi-threaded checks). Performance: Slightly slower than HashMap for a single thread, but significantly faster than Hashtable or SynchronizedMap. #Java #Programming #Backend #SoftwareEngineering #InterviewTips
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