LeetCode Challenge: Subsets (Power Set) Solution

Day 25/100 – LeetCode Challenge 🚀 Problem: Plus One Approach: Traversed digits from right to left Handled carry when the digit was 9 Created a new array only when all digits were 9 Time Complexity: O(n) Space Complexity: O(1) Key takeaway: Many array problems that involve arithmetic operations require careful carry handling from the end of the array. #LeetCode #100DaysOfCode #DSA #Java #ProblemSolving #InterviewPrep

Day 30/100 – LeetCode Challenge 🚀 Problem: Count Binary Substrings Approach: Counted consecutive groups of 0’s and 1’s For every adjacent pair of groups, added min(prevGroup, currGroup) to the result Avoided generating substrings explicitly Time Complexity: O(n) Space Complexity: O(1) Key takeaway: Many substring problems don’t require generating substrings — they can be solved by analyzing group patterns and transitions. #LeetCode #100DaysOfCode #DSA #Java #Strings #ProblemSolving

🚀 Day 14 of #100DaysOfCode Solved Merge Two Sorted Lists on LeetCode 🔗🔀 🧠 Key insight: Using a dummy (sentinel) node simplifies pointer handling and avoids edge cases when building the merged list. ⚙️ Approach: 🔹Initialize a dummy node to act as the start of the merged list 🔹Compare nodes from both lists one by one 🔹Attach the smaller node and move the pointer forward 🔹Append remaining nodes once one list is exhausted ⏱️ Time Complexity: O(n + m) 📦 Space Complexity: O(1) #100DaysOfCode #LeetCode #DSA #LinkedList #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 34/100 – LeetCode Challenge 🚀 Problem: Container With Most Water Approach: Used two pointers (left & right) Calculated area using min(height[left], height[right]) × width Moved the pointer pointing to the smaller height Updated maximum area during traversal Time Complexity: O(n) Space Complexity: O(1) Key takeaway: When maximizing area between two boundaries, moving the smaller boundary is the only way to potentially increase the result. #LeetCode #100DaysOfCode #DSA #Java #TwoPointers #ProblemSolving

Solved "Container With Most Water" on LeetCode today using the Two-Pointer Technique. 🚀 The key insight is that the area formed by two lines depends on the shorter height and the distance between them. Starting with pointers at both ends of the array, we compute the area and move the pointer at the smaller height inward to potentially find a taller boundary and maximize the area. This approach efficiently reduces the problem from O(n²) brute force to O(n) time with O(1) space. Problems like this are a great reminder that the right observation can drastically optimize a solution. 💡 #LeetCode #DSA #TwoPointers #Java #ProblemSolving

🚀 Day 16 of #100DaysOfCode Solved Remove Nth Node from End of List on LeetCode 🔗✂️ 🧠 Key insight: To remove the Nth node from the end, we need to carefully handle edge cases—especially when the node to remove is the head or when n equals the list length. ⚙️ Approach: 🔹First determine the length of the linked list 🔹Calculate the position from the start 🔹Traverse to the node just before the target 🔹Adjust pointers to remove the node safely ⏱️ Time Complexity: O(n) 📦 Space Complexity: O(1) #100DaysOfCode #LeetCode #DSA #LinkedList #Java #ProblemSolving #LearningInPublic #CodingJourney

🚀 Day 19 of #100DaysOfCode Solved 2. Add Two Numbers on LeetCode ➕🔗 (in-place linked list approach) 🧠 Key insight: Instead of creating a new list, we can reuse the longer linked list and perform addition in place, handling carry carefully across nodes. ⚙️ Approach: 🔹Calculate the size of both linked lists 🔹Use the longer list as the result list 🔹Traverse both lists, adding values with carry 🔹Continue processing remaining nodes of the longer list 🔹Append a new node if a carry remains at the end ⏱️ Time Complexity: O(max(n, m)) 📦 Space Complexity: O(1) (no extra list created) #100DaysOfCode #LeetCode #DSA #LinkedList #Java #ProblemSolving #LearningInPublic #CodingJourney

Day 13/100 – LeetCode Challenge 🚀 Solved Count Binary Substrings using an optimized O(n) approach by grouping consecutive characters and comparing segment lengths. Key takeaway: Instead of generating all substrings, identify patterns and reduce the problem to counting adjacent groups. Consistency > Motivation 💪 #100DaysOfCode #DSA #Java #LeetCode

🚀 Day 20 – #100DaysOfLeetCode Today’s problem: Product of Array Except Self (Medium) 🔹 Learned how to solve it in O(n) time 🔹 Without using division 🔹 Optimized space complexity The key idea was using prefix and suffix products instead of recalculating product every time. #Day20 #LeetCode #DSA #Java #CodingJourney