Java SQL Logical Thinking Practice Session

Day 5/50 | #50DaysOfCode 📍 Platform: LeetCode 💻 Language: Java ✅ 290. Word Pattern (Easy) Today’s problem focused on mapping relationships between characters and words. It helped strengthen my understanding of hash-based data structures and bijection logic. 🔎 Approach: Split the string s into individual words Check if the length of the pattern matches the number of words Use a HashMap to map each character in the pattern to a word Ensure that each character maps to only one unique word Also verify that no two characters map to the same word Return true if the mapping follows the pattern, otherwise false 📌 Example: Input: pattern = "abba", s = "dog cat cat dog" Output: true Explanation: 'a' → "dog" 'b' → "cat" This problem improved my understanding of HashMap usage, string splitting, and bijection mapping logic in Java. #DSA #LeetCode #Java #CodingJourney #ProblemSolving #Consistency #LearningJourney #50DaysOfCode #LinkedIn

Day 7/50 | #50DaysOfCode 📍 Platform: LeetCode 💻 Language: Java ✅ 167. Two Sum II - Input Array Is Sorted (Medium) Today’s problem focused on finding two numbers in a sorted array that sum up to a target. It helped reinforce the two-pointer technique and efficient array traversal. 🔎 Approach: Use two pointers: one at the start (left) and one at the end (right) of the array Calculate the sum of numbers at both pointers If sum equals target, return the 1-indexed positions [left+1, right+1] If sum < target, move left pointer forward If sum > target, move right pointer backward Continue until the solution is found 📌 Example: Input: numbers = [2,7,11,15], target = 9 Output: [1,2] Explanation: 2 + 7 = 9 → indices 1 and 2 This problem strengthened my understanding of two-pointer techniques, sorted arrays, and constant space solutions in Java. #DSA #LeetCode #Java #CodingJourney #ProblemSolving #Consistency #LearningJourney #50DaysOfCode #LinkedIn

🔁 Weekly Review Day Yesterday I was focused on revisiting fundamentals instead of learning something new. ✔️ Quick Java practice with arrays and small programs ✔️ SQL queries involving filtering and grouping I’m realizing that regular revision helps strengthen memory and highlights areas that still need more clarity. Small weekly reviews can make a big difference in long-term learning. #Java #SQL #LearningInPublic #Consistency #DeveloperJourney

🚀 DSA in Java — Day 78 📌 Problem Solved: Binary Tree Level Order Traversal Today I solved the Binary Tree Level Order Traversal problem on LeetCode using Breadth First Search (BFS) with a Queue. In this problem, we traverse the binary tree level by level from left to right. 🔹 Approach Used: Used a Queue data structure Added the root node to the queue Processed nodes level by level Stored each level's values inside a list Added the list to the final result 🔹 Key Concepts Practiced: ✔ Binary Trees ✔ Breadth First Search (BFS) ✔ Queue in Java ✔ Level-wise traversal This problem helped me understand how queues are used to process nodes level-wise in trees, which is very useful in many tree problems. Consistent practice is making tree problems much clearer day by day. 💻 Language: Java 📚 Platform: LeetCode #DSA #Java #BinaryTree #LeetCode #CodingJourney #WomenInTech #100DaysOfCode

🚀 DAY 75/150 — LEVEL ORDER TRAVERSAL IN ACTION! 🌳🔥 Day 75 of my 150 Days DSA Challenge in Java — halfway through the journey and stronger every day 💻🧠 Today I solved a problem that deepens my understanding of Binary Trees using BFS (Level Order Traversal). 📌 Problem Solved: Maximum Level Sum of a Binary Tree 📌 LeetCode: #1161 📌 Difficulty: Medium The task is to find the level of a binary tree where the sum of node values is maximum. If multiple levels have the same sum, return the smallest level number. 🔹 Approach Used I used Breadth-First Search (BFS) with a queue: • Traverse the tree level by level • For each level: Calculate the sum of all nodes • Track the level with the maximum sum This approach ensures we process nodes in the correct level order. ⏱ Complexity Time Complexity: O(n) Space Complexity: O(n) (due to queue storage) 🧠 What I Learned • BFS is ideal for problems involving levels in a tree • Queue plays a key role in level-order traversal • Tracking level-wise data helps solve many tree-based problems 💡 Key Takeaway This problem helped me understand how to process trees layer by layer, which is very useful for: Level-based problems Shortest path (in graphs) Tree traversals 🌱 75-Day Reflection At Day 75, I’ve learned: Arrays, Strings, Hashing Recursion & Backtracking Stack, Queue, Greedy And now diving deeper into Binary Trees The biggest lesson so far? 👉 Consistency beats everything. ✅ Day 75 completed 🚀 75 days to go 🔗 Java Solution on GitHub: 👉 https://lnkd.in/gcg9b9eT 💡 Halfway there — building logic, discipline, and confidence every day. #DSAChallenge #Java #LeetCode #BinaryTree #BFS #150DaysOfCode #ProblemSolving #CodingJourney #InterviewPrep #LearningInPublic #Consistency

🧠 Revision Day – Strengthening the Basics Again Yesterday was focused on strengthening fundamentals. ✔️ Java – Datatypes, Variables, If/else, Loops, 1D Arrays ✔️ SQL – SELECT, WHERE, AND/OR, BETWEEN, ORDER BY Instead of just reading, I rewrote examples and queries from memory. Real confidence comes from revisiting basics calmly and consistently. #Java #SQL #Consistency #LearningInPublic #BackendJourney

💡 A Quick & Powerful Look at Number Systems Ever wondered how your Java code actually stores numbers? 🤔 🖥️ Computers Think in Binary (Base 2) Only 0s and 1s. While humans use: 🔢 Decimal (Base 10) 🔡 Hexadecimal (Base 16) ⸻ 🔄 Let’s Convert 20 (Decimal) to Binary 20 → 10100 Now verify: 1×2⁴ + 0×2³ + 1×2² + 0×2¹ + 0×2⁰ = 16 + 4 = 20 ✅ Binary is just positional math. ⸻ 🧠 How Java Stores Integers In Java: • int = 32 bits • MSB (leftmost bit) = Sign bit Negative numbers use Two’s Complement: 1. Reverse all bits 2. Add 1 This allows subtraction to be performed using addition internally ⚡ ⸻ ⚙️ Bitwise Operators & → AND | → OR ^ → XOR ~ → NOT << → Left Shift → Signed Right Shift → Unsigned Right Shift ⸻ 🚀 Useful Bit Tricks ✔ Even/Odd → n & 1 ✔ Power of 2 → (n & (n-1)) == 0 ✔ Remove rightmost set bit → n & (n-1) ✔ Isolate rightmost set bit → n & (-n) ⸻ 🔥 Understanding bits improves: • Algorithm efficiency • Memory optimization • System-level thinking #Java #BitManipulation #Programming #BackendDevelopment

Day 33 of #100DaysOfLeetCode 💻✅ Solved #145. Binary Tree Postorder Traversal on LeetCode using Java. Approach: • Used recursion to perform postorder traversal • Followed Left → Right → Root order strictly • Traversed left subtree first • Then traversed right subtree • Added node value after visiting both subtrees Performance: ✓ Runtime: 0 ms (Beats 100.00% submissions) ✓ Memory: 43.12 MB (Beats 71.37% submissions) Key Learning: ✓ Clearly understood difference between preorder, inorder, and postorder ✓ Strengthened recursive tree traversal concepts ✓ Improved confidence in handling binary tree problems Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinaryTree #Recursion #TreeTraversal #ProblemSolving #CodingJourney #100DaysOfCode

📚 Today I Learned: Arrays in Java Today I explored the concept of Arrays in Java. Arrays allow us to store multiple values of the same data type in a single variable, which makes data management easier and more organized. 🔹 Arrays store multiple elements in one variable 🔹 Each element is accessed using an index 🔹 Index values start from 0 in Java 🔹 All elements in an array must have the same data type Example: int[] marks = {80, 75, 90}; Learning arrays helped me understand how to efficiently handle collections of data in programming. Looking forward to learning more about data structures and improving my coding skills. 🚀 #Java #JavaProgramming #Arrays #CodingJourney #LearnJava #ProgrammingBasics #SoftwareDevelopment #DeveloperJourney #CodingPractice #TechLearning #FutureDeveloper #CodeNewbie #100DaysOfCode #TechSkills #ProgrammingLife

Refactoring for Clarity: Array Manipulation in Java 👨💻 I’ve just finished a practical exercise on array manipulation. While the goal was simple (summing two arrays), I used it as an opportunity to apply improvements. - Method decomposition: Separated concerns into specialized methods (Read, Calculate, Display). - Input validation: Built a robust loop to handle invalid inputs and prevent crashes. - Data Formatting: Used printf to create a clear, readable results table. Small improvements in logic and organization make a huge difference in software quality. #Java #Algorithms #CleanCode #Backend #LearningToCode