Edit Distance: Convert word1 to word2 with min operations

🚀 Day 2/365 – Interleaving String (LeetCode 97) Today’s challenge was a classic Dynamic Programming problem – Interleaving String. 🔎 Problem Statement: Given three strings s1, s2, and s3, determine whether s3 is formed by interleaving s1 and s2 while maintaining the relative order of characters. 🧠 Key Learning At first glance, it looks like a simple string problem. But the real insight was realizing this is a 2D DP grid problem. If: len(s1) + len(s2) != len(s3) 👉 It’s immediately false. Then we build a DP table where: dp[i][j] = whether first i chars of s1 and first j chars of s2 can form first i + j chars of s3. This problem strengthened my understanding of: ✔️ State definition in DP ✔️ Transition logic ✔️ Space optimization (2D → 1D) ✔️ Thinking in terms of grid movement (down = s1, right = s2) 💡 Big Takeaway Most string problems are actually: 👉 Hidden Dynamic Programming 👉 About defining the correct state Consistency > Motivation. On to Day 3 💪 #365DaysOfCode #LeetCode #DynamicProgramming #Java #ProblemSolving #CodingJourney

Continuing with the Strings module. The focus shifted from basic string handling to actually solving problems using string logic. This involved counting specific characters, working with substrings, and understanding how nested loops apply to text just like they do with arrays. String s = "abcd"; for (int i = 0; i < s.length(); i++) {   for (int j = i + 1; j <= s.length(); j++) {     System.out.print(s.substring(i, j));   } System.out.println(); } Output: a ab abc abcd b bc bcd c cd d What became clear : - String problems often require nested loop thinking, similar to matrix traversal - Substrings help break a large problem into smaller continuous parts - Time complexity starts to matter once we generate all possible substrings - Logic matters more than syntax in problem-solving questions This felt like the point where Strings stopped being just text handling and started becoming real DSA practice. Continuing deeper into Strings. #Java #DSA #Strings #LearningInPublic #ProblemSolving #CodingJourney #Programming #JavaDeveloper #DeveloperJourney

💡 𝗝𝗮𝘃𝗮/𝐒𝐩𝐫𝐢𝐧𝐠 𝐁𝐨𝐨𝐭 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐓𝐢𝐩 🔥 💎 𝗣𝗿𝗲𝗳𝗲𝗿 𝗦𝘁𝗿𝗶𝗻𝗴𝗕𝘂𝗶𝗹𝗱𝗲𝗿 𝗢𝘃𝗲𝗿 𝗦𝘁𝗿𝗶𝗻𝗴 𝗖𝗼𝗻𝗰𝗮𝘁𝗲𝗻𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗟𝗼𝗼𝗽𝘀 🐌 𝗧𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝘄𝗶𝘁𝗵 𝗦𝘁𝗿𝗶𝗻𝗴 𝗖𝗼𝗻𝗰𝗮𝘁𝗲𝗻𝗮𝘁𝗶𝗼𝗻  Strings are immutable in Java, so the '+' operator creates a new String object with every concatenation. In loops, this creates thousands of temporary objects that need to be garbage collected. This dramatically impacts both performance and memory usage. 🔥 𝗪𝗵𝘆 𝗦𝘁𝗿𝗶𝗻𝗴𝗕𝘂𝗶𝗹𝗱𝗲𝗿 𝗶𝘀 𝗕𝗲𝘁𝘁𝗲𝗿 StringBuilder uses a mutable character buffer and modifies it in place without creating new objects. In benchmarks with 10,000 iterations, StringBuilder completes in ~4ms while '+' operator takes ~400ms. That's 100x faster with significantly lower memory allocation. ✅ 𝗪𝗵𝗲𝗻 𝘁𝗼 𝗨𝘀𝗲 𝗘𝗮𝗰𝗵 ◾ Use StringBuilder for loops and multiple concatenations. ◾ Use '+' for simple, single-line string building (2-3 strings). ◾ The compiler optimizes simple '+' usage, but not in loops. #java #springboot #programming #softwareengineering #softwaredevelopment

Mutable Strings are one of the most important concepts in Core Java, especially when it comes to performance and memory optimization. This revision cheat sheet covers: 🔹 What mutable strings are 🔹 StringBuffer and StringBuilder 🔹 Default capacity and resizing formula 🔹 Key methods: append(), capacity(), length(), delete(), insert(), reverse() 🔹 Internal capacity growth → (oldCapacity × 2) + 2 🔹 Difference between StringBuffer (Thread Safe) and StringBuilder (Faster, Non-Synchronized) 🔹 When to use each in real applications Understanding mutable strings helps in: ✔ Writing efficient code ✔ Avoiding unnecessary object creation ✔ Improving performance in large-scale applications ✔ Preparing confidently for technical interviews Strong fundamentals build strong developers. 🚀 #TAPACADEMY #Java #CoreJava #JavaProgramming #JavaDeveloper #SoftwareEngineering #Programming #Coding #Developers #codingchallenge #practicecode

100 Days of Coding Challenge – Day 3 📌 Problem: Set Matrix Zeroes 🧠 Concepts Used: 2D Arrays, Auxiliary Space, Matrix Traversal 💻 Language: Java 🔍 Platform: LeetCode Solved the Set Matrix Zeroes problem using an auxiliary space approach. I used two boolean arrays to track which rows and columns need to be zeroed, followed by a second pass to update the matrix. This helped keep the logic clear while avoiding unintended overwrites during traversal. 🔗 Code: https://lnkd.in/gVSfeKEi 🔗 Problem: https://lnkd.in/gpQWQuCg #100DaysOfCode #Day3 #Java #DSA #LeetCode #ProblemSolving #CodingJourney #Matrix #Arrays

🚀 Day 8/30 – Introduction to Dynamic Programming Today I solved a classic problem based on counting the number of distinct ways to climb stairs when you can take either one or two steps at a time. At its core, this problem highlights a fundamental Dynamic Programming concept: Each state depends on the results of previous states. Instead of recalculating values repeatedly (which would lead to exponential time complexity), I used a bottom-up DP approach: Define a recurrence relation Store intermediate results in an array Build the solution iteratively The transition relation follows: dp[i] = dp[i-1] + dp[i-2] This mirrors the Fibonacci pattern and ensures efficiency. 📊 Performance ✅ All test cases passed ⚡ 0 ms runtime (100% performance) ⏱ O(n) time complexity 📦 O(n) space complexity 📚 Key Takeaway Dynamic Programming is about breaking a complex problem into smaller overlapping subproblems and reusing computed results. Understanding the pattern behind the recurrence is more important than memorizing the formula. Day 8 complete. From basic logic to structured problem-solving — steady progress. #Day8 #30DaysOfCode #LeetCode #Java #DynamicProgramming #Algorithms #ProblemSolving #SoftwareEngineering #CodingJourney #Consistency

Abstract Class vs Interface : 🔹 Abstract Class ✔ Allows partial implementation ✔ Can contain fields & methods ✔ Supports single inheritance ✔ Best for closely related classes 🔹 Interface ✔ Defines only method contracts ✔ No implementation logic ✔ Supports multiple inheritance ✔ Best for defining capabilities #AbstractClass #Interface #OOPConcepts #Java #CSharp #DotNet #Programming #CodingInterview #SoftwareDevelopment #LearnToCode #TechExplained