LeetCode Challenge: Merge Sort Linked List

🚀 Day 22 of #100DaysOfCode Solved 34. Find First and Last Position of Element in Sorted Array on LeetCode 🔍 🧠 Key insight: To find both boundaries of a target in a sorted array, a single binary search isn’t enough. Running two binary searches—one for the leftmost and one for the rightmost occurrence—gives an optimal solution. ⚙️ Approach: 🔹Perform a binary search to find the first occurrence 🔹Perform another binary search to find the last occurrence 🔹Adjust search boundaries after finding the target to expand left/right ⏱️ Time Complexity: O(log n) 📦 Space Complexity: O(1) #100DaysOfCode #LeetCode #DSA #BinarySearch #Java #ProblemSolving #LearningInPublic #CodingJourney

Day 36/100 – LeetCode Challenge 🚀 Problem: 3Sum Closest Approach: Sorted the array Fixed one element and applied the two-pointer technique Tracked the closest sum by comparing absolute differences Returned immediately if an exact match was found Time Complexity: O(n²) Space Complexity: O(1) Key takeaway: Many optimization problems are variations of classic patterns. Understanding 3Sum deeply makes solving 3Sum Closest straightforward. #LeetCode #100DaysOfCode #DSA #Java #TwoPointers #ProblemSolving #InterviewPrep

Day 12/100 – LeetCode Challenge Problem Solved: Permutations Today’s problem was about generating all possible permutations of a given array of distinct integers. This is a classic backtracking problem where the objective is to build permutations step by step while ensuring each element is used exactly once in every arrangement. I implemented a recursive solution supported by a boolean array to track which elements were already included in the current permutation. At every recursive call, I select an unused element, add it to the current list, mark it as used, and continue exploring deeper. Once a permutation reaches the required length, it is added to the result set. Then comes the most important part — backtracking. I remove the last element and reset its state so other combinations can be explored. Time Complexity: O(n × n!) Space Complexity: O(n) excluding the output list #100DaysOfLeetCode #Java #Backtracking #Recursion #Algorithms #ProblemSolving #Consistency

Day 16/100 – LeetCode Challenge Problem: Merge Sorted Array Today’s problem involved merging two sorted arrays into one sorted array. Approach: Created a temporary array of size m + n Used two pointers to compare elements from both arrays Inserted the smaller element into the new array Copied remaining elements if any array still had values Finally copied the merged result back into nums1 Complexity: Time: O(m + n) Space: O(m + n) Concepts Practiced: Two-pointer technique Array traversal Merging sorted arrays #100DaysOfCode #LeetCode #DSA #Java #Arrays #ProblemSolving #CodingJourney

🚀 Day 24 of #100DaysOfCode Solved 167. Two Sum II – Input Array Is Sorted on LeetCode 🔢👉👈 🧠 Key insight: Because the array is already sorted, we can avoid hash maps and use a two-pointer approach to find the target sum efficiently. ⚙️ Approach: 🔹Initialize two pointers at the start and end of the array 🔹Calculate the sum of values at both pointers 🔹If the sum is too large → move the right pointer left 🔹If the sum is too small → move the left pointer right 🔹Stop when the target is found ⏱️ Time Complexity: O(n) 📦 Space Complexity: O(1) #100DaysOfCode #LeetCode #DSA #TwoPointers #Java #ProblemSolving #LearningInPublic #CodingJourney

🚀 Day 23/100 – LeetCode Challenge Today’s problem: Partitioning Into Minimum Number of Deci-Binary Numbers 🔹 Key Insight: The minimum number of deci-binary numbers required is equal to the maximum digit present in the string. 🔹 Approach: Traverse through each character in the string Convert it to integer (ch - '0') Track the maximum digit Return the maximum value 🔹 Time Complexity: O(n) 🔹 Space Complexity: O(1) ✨ Simple logic, but powerful observation! Instead of constructing numbers, we just analyze the digits. Consistency > Motivation 💪 #Day23 #100DaysOfCode #LeetCode #Java #ProblemSolving #CodingJourney

𝗬𝗼𝘂 𝗵𝗮𝘃𝗲 𝗯𝗲𝗲𝗻 𝘂𝘀𝗶𝗻𝗴 𝗕𝗶𝗻𝗮𝗿𝘆 𝗦𝗲𝗮𝗿𝗰𝗵 𝘄𝗿𝗼𝗻𝗴. It is not just for sorted arrays. The real definition — "Eliminate HALF the search space with each decision." That one shift in thinking unlocks 20+ LeetCode problems. Swipe to see the template, live code, and 7 problems you can now solve with one pattern. 👇 Save this. 🔖 #DSA #BinarySearch #Java #LeetCode #CodingInterview #DebugWithPurpose

Day 46/200 – LeetCode Challenge Multiply Strings Today’s focus was on implementing string-based multiplication without using built-in big integer libraries. The solution involved simulating manual multiplication using an integer array for positional sums. This approach ensured efficiency and accuracy even for very large inputs. Optimizing nested loops and handling digit positions carefully can significantly improve runtime in high-precision arithmetic problems. Continuing the 200-day journey with consistent progress #LeetCode #CodingChallenge #Java #ProblemSolving #200DaysOfCode #LearningEveryday

🚀 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

#Day67 of my second #100DaysOfCode Today’s problem pushed me to think carefully about comparisons and sorting logic. DSA • Solved Reverse Pairs (LeetCode 493) — count pairs (i, j) such that i < j and nums[i] > 2 * nums[j] • Brute force: check every pair using nested loops → O(n²) time • Optimal approach: Modified Merge Sort to count valid pairs during merge → O(2n log n) time, O(n) space • Key insight: count pairs across the left and right halves before merging. Another reminder of how divide-and-conquer + merge sort patterns appear in many hard problems. #DSA #Algorithms #LeetCode #MergeSort #Java #100DaysOfCode #WomenWhoCode #BuildInPublic #LearningInPublic