Java LeetCode 203: Remove Linked List Elements

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 34/180 | #180DaysOfCode 📍 LeetCode | 💻 Java Solved: 709. To Lower Case Used ASCII manipulation to convert uppercase letters to lowercase by adding 32, without using built-in functions. ⏱️ Time Complexity: O(n) 📦 Space Complexity: O(n) Strengthening understanding of character encoding and string manipulation basics. 💪 Consistency continues 🚀 #DSA #LeetCode #Java #CodingJourney #Consistency

Day 39 of #100DaysOfLeetCode 💻✅ Solved #258. Add Digits problem in Java. Approach: • Used a loop to repeatedly add all digits of the number • Extracted each digit using modulus (%) and divided the number by 10 • Stored the digit sum and repeated the process until the result became a single digit • Returned the final single digit as the answer Performance: ✓ Runtime: 1 ms (Beats 97.92% submissions) ✓ Memory: 42.52 MB Key Learning: ✓ Practiced digit extraction using modulus and division ✓ Understood how to repeatedly reduce a number to a single digit ✓ Strengthened problem-solving using loops and basic number manipulation Learning one problem every single day 🚀 #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 14/100 – LeetCode Challenge 🚀 Problem: #169 Majority Element   Difficulty: Easy   Language: Java   Approach: Sorting + Middle Element   Time Complexity: O(n log n)   Space Complexity: O(1) 🔍 Key Insight: The majority element appears **more than ⌊n / 2⌋ times** in the array. If we **sort the array**, the majority element must occupy the **middle position** because it appears more than half of the time. Therefore, the element at index **n/2** will always be the majority element. 🧠 Solution Brief: First sorted the array using `Arrays.sort()`. Since the majority element appears more than half of the array length, it will always be positioned at the middle index. Finally returned `nums[nums.length / 2]` as the majority element. 📌 What I Learned: Understanding problem constraints can simplify the solution significantly. Sometimes a simple observation (like majority occupying the middle after sorting) can avoid more complex implementations. #LeetCode #Day14 #100DaysOfCode #Java #DSA #Arrays #ProblemSolving #CodingJourney

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 84/365 ✔️ Solved LeetCode 26 – Remove Duplicates from Sorted Array using Java. A classic two-pointer problem that looks simple but really tests how well you handle in-place updates. Key takeaways from today: • Leveraged the two-pointer technique • Modified the array in-place with O(1) extra space • Preserved the relative order of elements • Reinforced how sorted arrays simplify logic Consistency > intensity. One problem a day, building strong fundamentals. On to the next 🚀 #Day84 #365DaysOfCode #LeetCode #Java #DSA #TwoPointers #ProblemSolving #Consistency

Day 13/100 – LeetCode Challenge 🚀 Problem: #283 Move Zeroes   Difficulty: Easy   Language: Java   Approach: Repeated Swapping / Zero Bubbling   Time Complexity: O(n²)   Space Complexity: O(1) 🔍 Key Insight: The goal is to move all **0s to the end** of the array while keeping the **relative order of non-zero elements unchanged**. Instead of creating a new array, the problem requires solving it **in-place**. 🧠 Solution Brief: First counted the total number of zeroes in the array. Then repeatedly traversed the array and whenever a **0** was found, swapped it with the next element. This process gradually pushes all zeroes toward the end of the array while preserving the order of the remaining elements. 📌 What I Learned: Even simple array problems require careful handling of constraints like **in-place modification** and **order preservation**. These problems also highlight the importance of thinking about **time complexity optimizations** for better performance. #LeetCode #Day13 #100DaysOfCode #Java #DSA #Arrays #ProblemSolving #CodingJourney

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 29 of #100DaysOfLeetCode 💻✅ Solved #22. Generate Parentheses on LeetCode using Java. Approach: • Used Backtracking to generate all valid combinations • Added "(" only if open brackets were available • Added ")" only when close brackets were greater than open • Ensured at every step that the parentheses remain balanced • Stopped recursion when both open and close counts reached zero Performance: ✓ Runtime: 3 ms (Beats 16.29% submissions) ✓ Memory: 45.18 MB (Beats 13.87% submissions) Key Learning: ✓ Strengthened understanding of Backtracking technique ✓ Learned how to maintain constraints during recursion ✓ Improved ability to build combinations using decision trees Learning one problem every single day 🚀 #Java #LeetCode #DSA #Backtracking #Recursion #ProblemSolving #CodingJourney #100DaysOfCode