LeetCode 148: Merge Sort on Linked List

🚀 Day 55 of #100DaysOfCode Solved 147. Insertion Sort List on LeetCode 🔗 🧠 Key Insight: We apply the classic Insertion Sort, but on a linked list instead of an array. The challenge is handling pointer manipulation efficiently. ⚙️ Approach: 1️⃣ Create a dummy node to act as the start of the sorted list 2️⃣ Traverse the original list node by node 3️⃣ For each node: Find its correct position in the sorted part Insert it there by updating pointers 🔁 This builds a sorted list incrementally ⏱️ Time Complexity: O(n²) 📦 Space Complexity: O(1) #100DaysOfCode #LeetCode #DSA #LinkedList #Sorting #Java #InterviewPrep #CodingJourney

🚀 Day 34 of #100DaysOfCode Solved 852. Peak Index in a Mountain Array on LeetCode ⛰️📈 🧠 Key Insight: A mountain array strictly increases to a peak and then decreases. Instead of scanning the whole array, we can use Binary Search to efficiently find the peak. ⚙️ Approach: 🔹Use binary search with two pointers left and right 🔹Compare arr[mid] with arr[mid + 1] 🔹If arr[mid] > arr[mid + 1] → peak is on the left side (including mid) 🔹Otherwise → peak is on the right side 🔹Continue until left == right, which gives the peak index ⏱️ Time Complexity: O(log n) 📦 Space Complexity: O(1) #100DaysOfCode #LeetCode #DSA #BinarySearch #Arrays #Java #ProblemSolving #InterviewPrep #LearningInPublic

🚀 Day 39 of #100DaysOfCode Solved 80. Remove Duplicates from Sorted Array II on LeetCode 🔢 🧠 Key Insight: The array is already sorted, and we need to ensure that each element appears at most twice, modifying the array in-place. ⚙️ Approach: 🔹Maintain a pointer i representing the position to place the next valid element 🔹Start iterating from index 2 🔹For each element nums[j], compare it with nums[i] 🔹If they are different, place the element at nums[i + 2] and move the pointer forward This ensures that no element appears more than twice while maintaining the sorted order. ⏱️ Time Complexity: O(n) 📦 Space Complexity: O(1) #100DaysOfCode #LeetCode #DSA #Arrays #TwoPointers #Java #ProblemSolving #InterviewPrep #LearningInPublic

🚀 Day 51 of #100DaysOfCode Solved 328. Odd Even Linked List on LeetCode 🔗 🧠 Key Insight: We need to rearrange the linked list such that: 🔹All odd-indexed nodes come first 🔹Followed by all even-indexed nodes 🔹While preserving the relative order ⚠️ Important: This is based on node position (index), not value. ⚙️ Approach: 1️⃣ Create two separate lists: 🔹odd → nodes at odd positions 🔹even → nodes at even positions 2️⃣ Traverse the list and distribute nodes accordingly 3️⃣ Connect: 🔹End of odd list → head of even list 4️⃣ Return the new head 🎯 This ensures a clean separation while maintaining order. ⏱️ Time Complexity: O(n) 📦 Space Complexity: O(1) (in-place re-linking) #100DaysOfCode #LeetCode #DSA #LinkedList #Algorithms #Java #InterviewPrep #CodingJourney

🚀 Day 84/100 – 𝐒𝐞𝐚𝐫𝐜𝐡 𝐢𝐧 𝐑𝐨𝐭𝐚𝐭𝐞𝐝 𝐒𝐨𝐫𝐭𝐞𝐝 𝐀𝐫𝐫𝐚𝐲 𝐈𝐈  🔍  𝐊𝐞𝐲 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Binary search works great on sorted arrays, but duplicates introduce ambiguity — making it harder to decide which half is sorted. 💡 𝐂𝐨𝐫𝐞 𝐈𝐝𝐞𝐚: Use modified binary search Identify the sorted half Handle duplicates by shrinking the search space ⚡ 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡: Find 𝐦𝐢𝐝 If 𝐭𝐚𝐫𝐠𝐞𝐭 𝐟𝐨𝐮𝐧𝐝 → 𝐫𝐞𝐭𝐮𝐫𝐧 𝐭𝐫𝐮𝐞 𝐇𝐚𝐧𝐝𝐥𝐞 𝐝𝐮𝐩𝐥𝐢𝐜𝐚𝐭𝐞𝐬 (𝐥𝐨𝐰++) Check which half is sorted Narrow down search accordingly #Day84 #100DaysOfCode #Java #DSA #LeetCode #BinarySearch #CodingJourney

🚀 Day 82 of #100DaysOfCode 🔍 Problem Solved: Find Minimum in Rotated Sorted Array Today I worked on a binary search based problem where we need to find the minimum element in a rotated sorted array in O(log n) time. 💡 Key Insight: If the array is already sorted (nums[low] <= nums[high]), then the first element is the minimum. Otherwise: If left half is sorted → minimum must be in right half If right half is unsorted → minimum lies there By carefully adjusting low and high, we narrow down the search space efficiently. 🧠 What I practiced: Modified Binary Search Identifying sorted halves Avoiding unnecessary comparisons #Java #DSA #BinarySearch #LeetCode #ProblemSolving #CodingJourney

#day332 of #1001daysofcode problem statement (0226): Invert Binary Tree The idea is to recursively swap the left and right child of every node in the tree. ⏱ Time Complexity: O(n) 🧠 Space Complexity: O(h) — recursion stack (h = height of tree) #1001DaysOfCode #DSA #Java #LeetCode #ProblemSolving Shivam Mahajan #leetcode

🚀 Day 50 / 100 | Median of Two Sorted Arrays Intuition: We are given two sorted arrays and need to find the median of the combined numbers. Since both arrays are already sorted, we can merge them in sorted order. Once we have the merged array, finding the median becomes simple. If the total number of elements is odd, the median is the middle element. If it's even, the median is the average of the two middle elements. Approach: Use two pointers to traverse both arrays. Compare the elements and insert the smaller one into a new array. Continue this process until all elements are merged. Finally, calculate the median based on the length of the merged array. Complexity: Time Complexity: O(n + m) Space Complexity: O(n + m) #100DaysOfCode #Java #DSA #LeetCode #ProblemSolving

🚀 Day 41 of #100DaysOfCode Solved 189. Rotate Array on LeetCode 🔄 🧠 Key Insight: Rotating an array by k steps to the right means the last k elements move to the front, while the remaining elements shift to the right. ⚙️ Approach: 1️⃣ Compute effective rotations using k % n 2️⃣ Store the last k elements in a temporary array 3️⃣ Shift the remaining n-k elements to the right 4️⃣ Copy the stored elements back to the beginning of the array This ensures the rotation happens in-place with controlled extra space. ⏱️ Time Complexity: O(n) 📦 Space Complexity: O(k) #100DaysOfCode #LeetCode #DSA #Arrays #Java #ProblemSolving #InterviewPrep #LearningInPublic

🚀 Day 33 of #100DaysOfCode Solved 25. Reverse Nodes in K-Group on LeetCode 🔁 🧠 Key Idea: Reverse nodes of a linked list k at a time, while keeping the remaining nodes unchanged if they are fewer than k. ⚙️ Approach: 🔹Traverse the list to check if k nodes exist. 🔹If fewer than k nodes remain → return the list as it is. 🔹Reverse the current k-group using a helper reverse function. 🔹Recursively apply the same logic to the remaining list. 🔹Connect the reversed group with the result of the recursive call. This approach makes the solution clean and modular by separating the logic of: 🔹Finding k nodes 🔹Reversing a segment 🔹Connecting segments ⏱️ Time Complexity: O(n) 📦 Space Complexity: O(n/k) (due to recursion stack) #100DaysOfCode #LeetCode #DSA #LinkedList #Java #ProblemSolving #CodingJourney #InterviewPrep