Palindrome Number LeetCode Challenge

Day 48 on LeetCode Minimum Size Subarray Sum 🎯✅ Today’s problem was a perfect application of the Sliding Window technique for optimizing subarray problems. 🔹 Approach Used in My Solution The goal was to find the smallest subarray length whose sum is greater than or equal to the target. Key idea in the solution: • Use two pointers low and high to maintain a dynamic window • Expand the window by moving high and adding elements to currentSum • Once the sum becomes ≥ target, start shrinking the window from the left (low) • Continuously update the minimum length during this process • If no valid subarray is found, return 0 This approach avoids brute force and ensures we process each element at most twice. ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Mastered the Sliding Window technique for variable window size • Learned how to optimize subarray problems from O(n²) to O(n) • Reinforced handling dynamic window expansion and contraction #LeetCode #DSA #Algorithms #DataStructures #SlidingWindow #Arrays #TwoPointers #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

🚀 Day 17/60 — LeetCode Discipline Problem Solved: 4Sum (Revision) Difficulty: Medium Today’s session revisited the classic k-Sum family problem — 4Sum. After solving 2Sum and 3Sum patterns previously, this problem naturally extends the idea by combining sorting with nested iteration and the two-pointer technique to efficiently identify unique quadruplets. The key challenge lies in managing duplicates carefully while keeping the solution efficient and structured. 💡 Focus Areas: • Strengthened k-Sum pattern understanding • Practiced sorting + two-pointer combination • Improved duplicate handling in multi-pointer problems • Reinforced nested iteration optimization • Focused on writing structured and readable code Problems like these highlight how mastering one pattern allows you to scale the same idea to more complex variations. #LeetCode #60DaysOfCode #100DaysOfCode #DSA #TwoPointers #Arrays #Algorithms #DataStructures #ProblemSolving #CodingJourney #SoftwareEngineering #Programming #Developers #TechCareers

Day 55 on LeetCode — Subarray Product Less Than K 📈✅ Today’s problem was a powerful application of the Sliding Window technique with multiplication-based constraints. 🔹 Approach Used in My Solution The goal was to count the number of contiguous subarrays where the product is less than k. Key idea in the solution: • Use two pointers l and r to maintain a dynamic window • Expand the window by multiplying the current element with prod • If prod ≥ k, shrink the window from the left by dividing elements • At each step, add (r - l + 1) to the count — representing all valid subarrays ending at r Also handled an important edge case: • If k ≤ 1, no valid subarray exists This approach ensures every element is processed efficiently without recomputation. ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Strengthened understanding of sliding window with multiplicative conditions • Learned how to count subarrays efficiently using window size • Reinforced handling edge cases early for cleaner logic #LeetCode #DSA #Algorithms #DataStructures #SlidingWindow #TwoPointers #Arrays #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

Day 57 on LeetCode Longest Repeating Character Replacement 🔤✅ Today’s problem was a powerful application of the Sliding Window technique with frequency tracking. 🔹 Approach Used in My Solution The goal was to find the longest substring where we can replace at most k characters to make all characters the same. Key idea in the solution: • Use a frequency array (size 26) to track character counts in the current window • Maintain a variable maxFreq → the highest frequency character in the window • Expand the window using r • If (window size - maxFreq) > k, shrink the window from the left (l) • Continuously update the maximum valid window size This works because we only care about keeping the window valid with at most k replacements. ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Mastered sliding window with dynamic constraints • Learned how tracking max frequency optimizes decisions • Strengthened understanding of window validation logic #LeetCode #DSA #Algorithms #DataStructures #SlidingWindow #Strings #TwoPointers #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

Day 50 on LeetCode — Maximum Average Subarray I 📊✅ Half-century milestone! 🚀 Today’s problem was a classic and clean application of the Sliding Window technique. 🔹 Approach Used in My Solution The goal was to find the maximum average of a subarray of size k. Key idea in the solution: • First, compute the sum of the first window of size k • Then slide the window forward by:   – Adding the next element   – Removing the element leaving the window • Continuously update the maximum sum encountered • Finally, divide the maximum sum by k to get the result This avoids recomputing sums and ensures an efficient solution. ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Mastered the fixed-size sliding window pattern • Learned how to optimize subarray sum problems • Reinforced thinking in terms of window reuse instead of recomputation #LeetCode #DSA #Algorithms #DataStructures #SlidingWindow #Arrays #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

🚀 LeetCode Daily Challenge 🔗 Problem: https://lnkd.in/giAcdv2U 💡 My thought process: This solution uses 3D dynamic programming to find the maximum coins that can be collected from the top-left to the bottom-right of a grid, allowing up to 2 neutralizations for negative cells. The state dp[i][j][k] stores the maximum coins reachable at cell (i, j) using k neutralizations. For each cell, transitions are taken from the left and top cells. If the current cell is negative, two options are considered: either neutralize it (if k > 0) and carry forward the previous value without adding the negative, or do not neutralize and add the cell value. For non-negative cells, the value is simply added to the best of the previous states. The starting cell is initialized separately based on whether it is neutralized or not. The final answer is the maximum value among dp[m-1][n-1][0], dp[m-1][n-1][1], and dp[m-1][n-1][2]. 👉 My Solution: https://lnkd.in/gZWS3Kns If you found this breakdown helpful, feel free to ⭐ the repo or connect with me on LinkedIn 🙂🚀 #️⃣ #leetcode #cpp #dsa #coding #problemsolving #engineering #BDRM #BackendDevWithRahulMaheswari

Day 52 on LeetCode — Minimum Recolors to Get K Consecutive Black Blocks 🧩✅ Today’s problem was another clean application of the Sliding Window technique with optimization. 🔹 Approach Used in My Solution The goal was to find the minimum number of recolors (W → B) needed to get k consecutive black blocks. Key idea in the solution: • Treat it as finding a window of size k with minimum 'W' (white blocks) • Count the number of 'W' in the first window of size k • Slide the window across the string:   – Remove the left character (if it was 'W')   – Add the new right character (if it is 'W') • Keep track of the minimum changes required This avoids recomputation and ensures an efficient linear solution. ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Strengthened understanding of fixed-size sliding window problems • Learned how to convert problems into min/max count in a window • Reinforced optimizing from brute force to O(n) solutions #LeetCode #DSA #Algorithms #DataStructures #SlidingWindow #Strings #TwoPointers #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

Day 65 on LeetCode Sort Characters By Frequency 🔤📊✅ Today’s problem focused on combining hash maps with custom sorting. 🔹 Approach Used in My Solution The goal was to sort characters in a string based on their frequency in descending order. Key idea in the solution: • Use a hash map to count frequency of each character • Store (character, frequency) pairs in a vector • Apply custom sorting based on frequency (descending order) • Build the result string by repeating characters according to their frequency This approach efficiently organizes characters by importance (frequency). ⚡ Complexity: • Time Complexity: O(n log n) (due to sorting) • Space Complexity: O(n) 💡 Key Takeaways: • Practiced frequency counting using hash maps • Learned how to apply custom comparators in sorting • Reinforced building results based on frequency-driven logic #LeetCode #DSA #Algorithms #DataStructures #HashMap #Sorting #Strings #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

🚀 19 of #100DaysOfCode Solved LeetCode 1456 – Maximum Number of Vowels in a Substring of Given Length today. 🔍 Approach: Used the Sliding Window Technique to efficiently track the number of vowels in a substring of size k. Instead of recalculating vowels for every substring, we adjust the count as the window slides forward. 💡 Key Idea: Add the new character entering the window. Remove the character leaving the window. Keep track of the maximum vowel count. ⏱ Time Complexity: O(n) 📦 Space Complexity: O(1) This approach optimizes the brute-force solution and makes the algorithm scalable for large inputs. Consistent practice is helping me strengthen my problem-solving and data structures fundamentals. #leetcode #dsaalgorithms #slidingwindow #cpp #codingpractice #programming #softwaredevelopment #100daysofcode #developers #techlearning

Day 51 on LeetCode — Permutation in String 🔤✅ Today’s problem was a strong application of the Sliding Window + Frequency Count technique. 🔹 Approach Used in My Solution The goal was to check if any permutation of s1 exists as a substring in s2. Key idea in the solution: • Use two frequency arrays (size 26) to track character counts • Initialize frequencies for s1 and the first window of s2 • Compare both frequency arrays — if equal, permutation exists • Slide the window across s2:   – Add incoming character   – Remove outgoing character • Check for a match at each step This ensures we efficiently check all substrings of size k without recomputing frequencies. ⚡ Complexity: • Time Complexity: O(n) • Space Complexity: O(1) 💡 Key Takeaways: • Mastered sliding window with fixed-size frequency arrays • Learned how to efficiently detect anagram/permutation patterns • Reinforced optimizing from brute force to linear-time solutions #LeetCode #DSA #Algorithms #DataStructures #SlidingWindow #Strings #Hashing #FrequencyArray #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney