Two Pointer Technique for Two Sum II on LeetCode

Day 36 of #100DaysOfLeetCode 💻✅ Solved #111. Minimum Depth of Binary Tree on LeetCode using Java. Approach: • Used recursive approach to calculate minimum depth • Returned 0 when root is null (base case) • If one subtree is null, avoided taking minimum of 0 (handled edge case carefully) • Returned 1 + minimum depth of valid subtree • Ensured correct handling of skewed trees Performance: ✓ Runtime: 6 ms ✓ Memory: 82.20 MB Key Learning: ✓ Understood difference between minimum depth and maximum depth logic ✓ Learned importance of handling null subtree cases correctly ✓ Improved confidence in solving binary tree recursion problems Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinaryTree #Recursion #TreeProblems #ProblemSolving #CodingJourney #100DaysOfCode

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

Day 51 of #100DaysOfLeetCode 💻✅ Solved #217. Contains Duplicate problem in Java. Approach: • Sorted the array using Arrays.sort() • Traversed the array starting from index 1 • Compared each element with its previous element • If any two adjacent elements are equal, returned true • If no duplicates are found, returned false Performance: ✓ Runtime: 24 ms (Beats 26.49% submissions) ✓ Memory: 76.56 MB (Beats 96.73% submissions) Key Learning: ✓ Practiced sorting-based approach for detecting duplicates ✓ Learned how sorting helps bring duplicate elements together ✓ Strengthened understanding of array traversal techniques Learning one problem every single day 🚀 #Java #LeetCode #DSA #Arrays #ProblemSolving #CodingJourney #100DaysOfCode

Day 31 of #100DaysOfLeetCode 💻✅ Solved #94. Binary Tree Inorder Traversal on LeetCode using Java. Approach: • Used recursion to perform inorder traversal • Followed Left → Root → Right order strictly • Traversed left subtree first before processing current node • Stored node values in a list during traversal • Returned the final list after complete traversal Performance: ✓ Runtime: 0 ms (Beats 100.00% submissions) ✓ Memory: 42.76 MB (Beats 98.30% submissions) Key Learning: ✓ Strengthened understanding of tree traversal patterns ✓ Improved clarity on recursion stack behavior ✓ Reinforced difference between preorder, inorder, and postorder traversal Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinaryTree #Recursion #TreeTraversal #ProblemSolving #CodingJourney #100DaysOfCode

Day 30 of #100DaysOfLeetCode 💻✅ Solved #108. Convert Sorted Array to Binary Search Tree on LeetCode using Java. Approach: • Used Divide and Conquer strategy • Selected the middle element as the root to maintain balance • Recursively built the left subtree using left half of array • Recursively built the right subtree using right half of array • Ensured the tree remains height-balanced at every step Performance: ✓ Runtime: 0 ms (Beats 100.00% submissions) ✓ Memory: 45.18 MB (Beats 44.10% submissions) Key Learning: ✓ Understood how sorted arrays can directly map to balanced BST ✓ Strengthened recursion fundamentals in tree construction ✓ Improved understanding of height-balanced binary trees Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinarySearchTree #Recursion #DivideAndConquer #ProblemSolving #CodingJourney #100DaysOfCode

Day 34 of #100DaysOfLeetCode 💻✅ Solved #110. Balanced Binary Tree on LeetCode using Java. Approach: • Used a bottom-up recursive approach to calculate height • Returned -1 immediately if any subtree is unbalanced • Compared left and right subtree heights at each node • Checked if the height difference is greater than 1 • Stopped early to optimize unnecessary computations Performance: ✓ Runtime: 0 ms (Beats 100.00% submissions) ✓ Memory: 45.33 MB (Beats 95.41% submissions) Key Learning: ✓ Understood how to combine height calculation with balance checking ✓ Learned early termination technique in recursion ✓ Improved problem-solving for tree-based recursive problems Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinaryTree #Recursion #TreeProblems #ProblemSolving #CodingJourney #100DaysOfCode

Day 45 of #100DaysOfLeetCode 💻✅ Solved Simple #268. Missing Number problem in Java. Approach: • Calculated the expected sum of numbers from 0 to n using the formula n(n+1)/2 • Traversed the array and calculated the actual sum of the elements • Subtracted the actual sum from the expected sum • The difference gives the missing number in the array Performance: ✓ Runtime: 0 ms (Beats 100% submissions) 🚀 ✓ Memory: 47.60 MB (Beats 29.84% submissions) Key Learning: ✓ Practiced using mathematical formulas to simplify problems ✓ Learned how sum comparison can help find a missing element efficiently ✓ Strengthened problem-solving skills with arrays Learning one problem every single day 🚀 #Java #LeetCode #DSA #Arrays #ProblemSolving #CodingJourney #100DaysOfCode

Day 32 of #100DaysOfLeetCode 💻✅ Solved #144. Binary Tree Preorder Traversal on LeetCode using Java. Approach: • Used recursion to perform preorder traversal • Followed Root → Left → Right order strictly • Added node value before traversing subtrees • Traversed left subtree first, then right subtree • Stored values in a list during traversal Performance: ✓ Runtime: 0 ms (Beats 100.00% submissions) ✓ Memory: 42.83 MB (Beats 96.77% submissions) Key Learning: ✓ Strengthened understanding of preorder traversal pattern ✓ Clearly differentiated preorder from inorder traversal ✓ Improved recursive tree traversal implementation skills Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinaryTree #Recursion #TreeTraversal #ProblemSolving #CodingJourney #100DaysOfCode

Day 44 of #100DaysOfLeetCode 💻✅ Solved Very Simple #169. Majority Element problem in Java. Approach: • Sorted the given array using Arrays.sort() • Observed that the majority element appears more than n/2 times • After sorting, the majority element will always be present at index n/2 • Returned the element at nums[n/2] Performance: ✓ Runtime: 7 ms (Beats 42.86% submissions) ✓ Memory: 55.96 MB (Beats 16.21% submissions) Key Learning: ✓ Understood how sorting can help identify the majority element ✓ Learned the property that the majority element always occupies the middle position after sorting ✓ Practiced array manipulation and problem solving in Java Learning one problem every single day 🚀 #Java #LeetCode #DSA #Arrays #ProblemSolving #CodingJourney #100DaysOfCode

Day 1/100 – LeetCode Challenge 🚀 Problem: #867 Transpose Matrix   Difficulty: Easy   Language: Java   Approach: Nested Loop with Index Swapping   Time Complexity: O(m × n)   Space Complexity: O(m × n) 🔍 Key Insight: The transpose of a matrix swaps rows and columns. If original matrix is m × n, the result will be n × m. Careful index handling is important to avoid dimension errors. 🧠 Solution Brief: Created a new matrix with reversed dimensions. Traversed the original matrix using nested loops. Assigned result[j][i] = matrix[i][j] to swap row and column indices. Returned the transposed matrix. this solution is basicaly bruteforce approach 📌 What I Learned: Even simple matrix problems improve understanding of 2D array traversal and index manipulation. Consistency starts today — 99 more days to go 💪 #LeetCode #Day1 #100DaysOfCode #Java #DSA #ProblemSolving #CodingJourney #LearningInPublic