Solved Valid Parentheses in Java with Stack

Day 20 of #100DaysOfLeetCode 💻✅ Solved #21. Merge Two Sorted Lists problem on LeetCode in Java. Approach: • Handled edge cases where either list is empty • Used a dummy node to simplify merging logic • Maintained a pointer current to build the new list step-by-step • Compared nodes from both lists and linked the smaller one • Connected any remaining nodes after one list ends • Returned dummy.next as the new head of the merged list Performance: ✓ Runtime: 0 ms (Beats 100% submissions) ✓ Memory: 44.26 MB (Beats 75% submissions) Key Learning: ✓ Strengthened understanding of linked list pointer manipulation ✓ Learned to merge two lists without creating extra nodes ✓ Improved confidence in multi-pointer problems and list traversal Learning one problem every single day 🚀 #Java #LeetCode #DSA #ProblemSolving #CodingJourney #100DaysOfCode

Day 26 of #100DaysOfLeetCode 💻✅ Solved #203. Remove Linked List Elements on LeetCode using Java. Approach: • Handled edge cases by removing matching nodes from the beginning of the list • Traversed the linked list using a pointer • Checked the next node’s value instead of the current node • If value matched, updated links to skip the node • Maintained in-place modification without using extra data structures Performance: ✓ Runtime: 1 ms (Beats 95.94% submissions) ✓ Memory: 47.62 MB Key Learning: ✓ Improved understanding of linked list pointer manipulation ✓ Learned how to handle head node edge cases carefully ✓ Strengthened in-place deletion logic in singly linked lists Learning one problem every single day 🚀 #Java #LeetCode #DSA #LinkedList #ProblemSolving #CodingJourney #100DaysOfCode

Day 27 of #100DaysOfLeetCode 💻✅ Solved #83. Remove Duplicates from Sorted List on LeetCode using Java. Approach: • Utilized the fact that the linked list is already sorted • Traversed the list using a single pointer • Compared current node value with next node value • If duplicate found, skipped the next node by updating links • Continued traversal until reaching the end of the list Performance: ✓ Runtime: 0 ms (Beats 100% submissions) ✓ Memory: 45.30 MB (Beats 85.70% submissions) Key Learning: ✓ Understood how sorting simplifies duplicate removal logic ✓ Strengthened pointer manipulation skills in linked lists ✓ Learned efficient in-place modification without extra space Learning one problem every single day 🚀 #Java #LeetCode #DSA #LinkedList #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 25 of #100DaysOfLeetCode 💻✅ Solved #167. Two Sum II – Input Array Is Sorted on LeetCode using Java. Approach: • Used Two Pointer technique since the array is already sorted • Initialized one pointer at the beginning and one at the end • Calculated the sum of both elements • If sum < target, moved left pointer forward • If sum > target, moved right pointer backward • Returned 1-based indices as required in the problem Performance: ✓ Runtime: 1 ms (Efficient with O(n) time complexity) ✓ Memory: Constant extra space (O(1)) Key Learning: ✓ Understood when to apply Two Pointer technique instead of HashMap ✓ Improved ability to optimize space complexity ✓ Strengthened pattern recognition for sorted array problems Learning one problem every single day 🚀 #Java #LeetCode #DSA #TwoPointers #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

🚀 #100DaysOfCode | Day 35 📌 LeetCode : Minimum Depth of Binary Tree Today I solved the Minimum Depth of Binary Tree problem using Java. The goal was to find the shortest path from the root node to the nearest leaf node. I applied a recursive approach while carefully handling edge cases where one subtree is null. Instead of directly taking the minimum of both sides, I ensured the solution correctly skips null paths to avoid incorrect depth calculations. 📌 Key takeaways: 🔹 Understood the difference between minimum and maximum depth logic 🔹 Learned the importance of handling null child nodes 🔹 Strengthened recursion and tree traversal concepts 🔹 Improved problem-solving accuracy in edge cases This problem helped me think more clearly about tree structures and reinforced the importance of precise base conditions in recursion. #Java #LeetCode #DSA #ProblemSolving #CodingJourney #100DaysOfCode

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 20/180 | #180DaysOfCode 📍 LeetCode | 💻 Java Solved: 350. Intersection of Two Arrays II Used sorting + two-pointer technique to efficiently find common elements appearing in both arrays while maintaining correct frequency. ⏱️ Time Complexity: O(n log n + m log m) 📦 Space Complexity: O(min(n, m)) (for storing the intersection) Strengthening understanding of array traversal and two-pointer pattern through consistent practice. 💪 Consistency keeps the progress moving 🚀 #DSA #LeetCode #Java #CodingJourney #Consistency

Day 12 of #100DaysOfLeetCode 💻✅ Solved #326. Power of Three problem in Java. Approach: • Checked if the number is less than or equal to zero (not a power of three) • Continuously divided the number by 3 while it was divisible • Verified whether the final value becomes 1 • Avoided recursion and used iteration for better efficiency Performance: ✓ Runtime: 8 ms (Beats 86.60% submissions) ✓ Memory: 46.35 MB Key Learning: ✓ Strengthened understanding of number divisibility logic ✓ Learned efficient validation of power-based numbers ✓ Improved problem-solving using iterative reduction Learning one problem every day 🚀 #Java #LeetCode #DSA #ProblemSolving #CodingJourney #100DaysOfCode