Day 38 of #100DaysOfLeetCode 💻✅ Solved #222. Count Complete Tree Nodes problem in Java. Approach: • Used recursion to traverse the binary tree • Counted the current node and recursively counted nodes in left and right subtrees • Added the counts to get the total number of nodes • Returned 0 when the node is null to stop recursion Performance: ✓ Runtime: 0 ms (Beats 100% submissions) ✓ Memory: 44 MB Key Learning: ✓ Practiced recursion with binary trees ✓ Understood how tree traversal helps count nodes in a tree ✓ Improved recursive thinking while solving tree problems Learning one problem every single day 🚀 #Java #LeetCode #DSA #ProblemSolving #CodingJourney #100DaysOfCode
Java LeetCode #222: Count Complete Tree Nodes
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Day 43 of #100DaysOfLeetCode 💻✅ Solved #100. Same Tree problem in Java. Approach: • Used recursion to compare both binary trees simultaneously • If both nodes are null, returned true • If one node is null and the other is not, returned false • Checked whether the values of both nodes are equal • Recursively compared the left subtrees and right subtrees Performance: ✓ Runtime: 0 ms (Beats 100% submissions) 🚀 ✓ Memory: 43.10 MB (Beats 30.15% submissions) Key Learning: ✓ Practiced recursive traversal of binary trees ✓ Learned how to compare two trees node by node ✓ Strengthened understanding of tree recursion logic Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinaryTrees #ProblemSolving #CodingJourney #100DaysOfCode
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Day 47 of #100DaysOfLeetCode 💻✅ Solved #101. Symmetric Tree problem in Java. Approach: • Used recursion to compare the left and right subtrees of the root • If both nodes are null, the tree is symmetric at that level • If one node is null and the other is not, the tree is not symmetric • Compared the values of both nodes • Recursively checked left.left with right.right and left.right with right.left to verify mirror structure Performance: ✓ Runtime: 0 ms (Beats 100% submissions) ✓ Memory: 43.62 MB (Beats 48.60% submissions) Key Learning: ✓ Practiced mirror comparison in binary trees ✓ Learned how recursion can verify symmetry between two subtrees ✓ Strengthened understanding of tree traversal and structural comparison Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinaryTrees #ProblemSolving #CodingJourney #100DaysOfCode
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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
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Day 42 of #100DaysOfLeetCode 💻✅ Solved #704. Binary Search problem in Java. Approach: • Since the array is already sorted, applied the Binary Search algorithm • Initialized two pointers: left at the start and right at the end of the array • Calculated the middle index using (left + right) / 2 • If the middle element equals the target, returned the index • If the middle element is smaller than the target, moved the left pointer to mid + 1 • If the middle element is greater than the target, moved the right pointer to mid - 1 • Continued until the target was found or the search space became empty Performance: ✓ Runtime: 0 ms (Beats 100% submissions) 🚀 ✓ Memory: 48.32 MB (Beats 68.26% submissions) Key Learning: ✓ Practiced Binary Search with O(log n) time complexity ✓ Learned how pointer adjustments reduce the search space efficiently ✓ Strengthened understanding of searching algorithms in sorted arrays Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinarySearch #ProblemSolving #CodingJourney #100DaysOfCode
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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
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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
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Day 46 of #100DaysOfLeetCode 💻✅ Solved #374. Guess Number Higher or Lower problem in Java. Approach: • Used Binary Search to efficiently guess the number. • Calculated mid using low + (high - low) / 2 to avoid overflow. • Used the guess(mid) API to check if the number is higher, lower, or correct. • Updated the search range accordingly until the number was found. Performance: ✓ Runtime: 0 ms (Beats 100% submissions) 🚀 ✓ Memory: 41.68 MB (Beats 97.84% submissions) Key Learning: ✓ Practiced implementing binary search on a real problem ✓ Learned how to safely calculate mid to prevent integer overflow ✓ Strengthened problem-solving skills with search algorithms Learning one problem every single day 🚀 #Java #LeetCode #DSA #BinarySearch #ProblemSolving #CodingJourney #100DaysOfCode
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Day 40 of #100DaysOfLeetCode 💻✅ Solved #112. Path Sum problem in Java. Approach: • Used recursion to traverse the binary tree from root to leaf • Subtracted the current node value from the targetSum at each step • Checked whether the current node is a leaf node (no left and right children) • If the remaining sum becomes 0 at the leaf node, returned true • Otherwise continued checking the left and right subtrees recursively Performance: ✓ Runtime: 1 ms (Beats 6.06% submissions) ✓ Memory: 45.18 MB (Beats 27.94% submissions) Key Learning: ✓ Practiced root-to-leaf traversal in binary trees ✓ Learned how to track the remaining sum during recursion ✓ Improved understanding of recursive tree problem solving Learning one problem every single day 🚀 #Java #LeetCode #DSA #ProblemSolving #CodingJourney #100DaysOfCode
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Day 63 of #100DaysOfLeetCode 💻✅ Solved #2085. Count Common Words With One Occurrence problem in Java. Approach: • Iterated through each word in the first array • Avoided duplicate checks by ensuring each word is processed only once • Counted occurrences of the current word in both arrays • If the word appears exactly once in both arrays, incremented the result • Returned the final count Performance: ✓ Runtime: 88 ms (Beats 7.45% submissions) ✓ Memory: 46.06 MB (Beats 93.07% submissions) Key Learning: ✓ Practiced handling duplicates and frequency counting ✓ Improved understanding of string comparison in arrays ✓ Learned importance of optimizing nested loop solutions Learning one problem every single day 🚀 #Java #LeetCode #DSA #Strings #Arrays #ProblemSolving #CodingJourney #100DaysOfCode
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🚀 Day 92 – #100DaysOfCode Qn. Combination Sum III Today I worked on the Combination Sum III problem using recursion and backtracking in Java. 🔹 Problem Summary: Find all possible combinations of k numbers that add up to n, using numbers 1–9 only once. 🔹 My Approach: Used recursion to explore all possible number combinations. Maintained a running sum and a temporary list. When the sum equals n and the list size equals k, the combination is added to the result. Used a HashSet to avoid duplicate combinations. 🔹 Key Learning: This problem helped me strengthen my understanding of: Backtracking Recursive decision trees Managing state during recursion (adding/removing elements) 📌 Next Goal: Optimize the solution further by avoiding the HashSet and pruning unnecessary recursive calls. #Day92 #LeetCode #DSA #Java #Recursion #Backtracking #CodingJourney
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