Alternating Binary String Minimum Flips

Day 82/100 – LeetCode Challenge ✅ Problem: #43 Multiply Strings Difficulty: Medium Language: Java Approach: Manual Multiplication with Result Array Time Complexity: O(n × m) Space Complexity: O(n + m) Key Insight: Multiply digits from right to left (least significant first). Store intermediate results in array where index i + j + 1 holds current digit. Handle carry by adding to previous index. Solution Brief: Edge case: if either number is "0", return "0". Created result array of size n1 + n2 (max possible digits). Nested loops multiply each digit of num1 with each digit of num2. Accumulated results with proper carry handling. Built final string skipping leading zeros. #LeetCode #Day82 #100DaysOfCode #Math #String #Java #Algorithm #CodingChallenge #ProblemSolving #MultiplyStrings #MediumProblem #Multiplication #Array #DSA

🚀 Day 43 of DSA |Check if Binary String Has at Most One Segment of Ones. Given a binary string without leading zeros, we need to check whether it contains at most one contiguous segment of '1's. Example Input: "1001" → Output: false Input: "110" → Output: true 💡 Key Insight If a '0' appears after the first segment of '1's and we encounter another '1', it means a new segment started. 🧠 Approach • Traverse the string • Once '0' appears after '1', mark it • If another '1' appears afterwards → return false ⏱ Time Complexity: O(n) 📦 Space Complexity: O(1) This problem highlights how pattern observation can simplify string traversal problems. #DSA #Java #LeetCode #CodingPractice #ProblemSolving

🚀 DSA Practice – Longest Subarray with Sum = K (Positive Numbers) Today I practiced a classic Sliding Window / Two Pointer problem. Problem: Find the longest subarray whose sum equals K, when the array contains only positive numbers. 💡 Key Idea: * Since all numbers are positive, we can use the sliding window technique: Expand the window by moving the right pointer. * If the sum becomes greater than k, shrink the window using the left pointer. Whenever sum == k, update the maximum length. ⚡ Time Complexity: O(n) ⚡ Space Complexity: O(1) Example: arr = [1, 2, 3, 1, 1, 1, 1, 4, 2, 3] k = 3 Longest subarray: [1, 1, 1] Length = 3 This problem is a great example of how understanding constraints (positive numbers) allows us to replace complex approaches like HashMap + Prefix Sum with a simpler and more efficient Sliding Window technique. #DSA #Algorithms #Java #SlidingWindow #LeetCode #SoftwareEngineering

Day 87/100 – LeetCode Challenge ✅ Problem: #867 Transpose Matrix Difficulty: Easy Language: Java Approach: Direct Matrix Swapping Time Complexity: O(m × n) Space Complexity: O(m × n) for result matrix Key Insight: Transpose swaps rows and columns: transposed[i][j] = matrix[j][i]. New matrix dimensions: col × row (original dimensions swapped). Solution Brief: Created result matrix with dimensions col × row. Nested loops assign each element to swapped position. Returned transposed matrix. #LeetCode #Day87 #100DaysOfCode #Matrix #Java #Algorithm #CodingChallenge #ProblemSolving #TransposeMatrix #EasyProblem #Array #2DArray #DSA

Day 56/100 | #100DaysOfDSA 🧠⚡ Today’s problem: String Compression A clean in-place array manipulation problem. Core idea: Compress consecutive repeating characters and store the result in the same array. Approach: • Traverse the array using a pointer • Count consecutive occurrences of each character • Write the character to the array • If count > 1 → write its digits one by one • Move forward and repeat Key insight: We don’t need extra space — just carefully manage read & write pointers. Time Complexity: O(n) Space Complexity: O(1) Big takeaway: In-place algorithms require precise pointer control but give optimal space efficiency. Mastering these improves real-world memory optimization skills. 🔥 Day 56 done. #100DaysOfCode #LeetCode #DSA #Algorithms #Strings #TwoPointers #InPlace #Java #CodingJourney #ProblemSolving #InterviewPrep #TechCommunity

Day 65: The "One-Liner" Win 🎯 Problem 1784: Check if Binary String Has at Most One Segment of Ones Today was a lesson in simplifying logic. The challenge: check if a binary string contains more than one contiguous segment of '1's, given that the string starts with '1'. The Strategy: • Observation: If there are multiple segments of '1's, they must be separated by at least one '0'. • The Pattern: In a string starting with '1', any "new" segment of ones would look like "01" somewhere in the string. • The Execution: A simple !s.contains("01") handles the entire check. Sometimes we hunt for complex algorithms when a single string method is the ultimate counter. Clean, readable, and passed all test cases. 🚀 #LeetCode #Java #StringManipulation #Coding #Efficiency #DailyCode

Day 39 of Daily DSA 🚀 Solved LeetCode 1446: Consecutive Characters ✅ Problem: The power of a string is the maximum length of a non-empty substring that contains only one unique character. Given a string s, return its power. Rules: * Substring must be non-empty * Substring must contain only one unique character * Return the maximum such length Approach: Used a simple linear scan to track the current streak of consecutive identical characters and update the maximum. Steps: 1. Initialize max and count both to 1 2. Iterate from index 1 onwards 3. If current character equals previous → increment count 4. Else → reset count to 1 5. Update max at every step 6. Return max ⏱ Complexity: • Time: O(n) • Space: O(1) 📊 LeetCode Stats: • Runtime: 29 ms (Beats 2.02%) • Memory: 45.33 MB Sometimes the simplest sliding window — just two variables — is all you need to solve a problem cleanly. #DSA #LeetCode #Java #SlidingWindow #Strings #CodingJourney #ProblemSolving

Day 27/75 — Shortest Subarray with Sum ≥ K Today I solved a challenging problem involving prefix sums and a monotonic deque. Problem: Find the length of the shortest subarray whose sum is at least K. Challenge: A standard sliding window does not work because the array may contain negative numbers. Approach: • Compute prefix sums • Use a deque to store indices of increasing prefix sums • Remove useless prefixes that cannot produce better answers Key condition: prefix[j] - prefix[i] ≥ K Time Complexity: O(n) Space Complexity: O(n) This problem introduced the monotonic deque technique, which is useful in many advanced array problems. 27/75 🚀 #Day27 #DSA #Algorithms #Java #LeetCode #ProblemSolving

Day 46/75 — Frequency of the Most Frequent Element Today’s problem was about maximizing the frequency of an element using at most k increments. Approach: • Sort the array • Use sliding window • Maintain sum of current window • Expand right pointer • Shrink window when operations exceed k Key logic: while ((long) nums[right] * (right - left + 1) - total > k) {  total -= nums[left];  left++; } maxFreq = Math.max(maxFreq, right - left + 1); Time Complexity: O(n log n) (sorting) Space Complexity: O(1) Key Insight: Make all elements in window equal to the largest element — check if cost ≤ k. 46/75 🚀 #Day46 #DSA #SlidingWindow #TwoPointers #Java #Algorithms #LeetCode

Day 38 of Daily DSA 🚀 Solved LeetCode 1897: Redistribute Characters to Make All Strings Equal ✅ Problem: Given an array of strings, determine if you can make every string equal by moving any character from one string to any position in another string. Rules: * You can pick two distinct indices i and j and move any character from words[i] to any position in words[j] * Any number of operations are allowed * Return true if all strings can be made equal, false otherwise Approach: Used a HashMap to count the total frequency of every character across all strings. If every character's count is divisible by the number of strings, equal redistribution is possible. Steps: 1. Concatenate all strings into one using StringBuilder 2. Count the frequency of each character using a HashMap 3. For every character count, check if it is divisible by the number of words 4. If any count is not divisible → return false 5. Otherwise → return true ⏱ Complexity: • Time: O(n * m) — n = number of words, m = average word length • Space: O(1) — at most 26 characters in the map 📊 LeetCode Stats: • Runtime: 12 ms (Beats 17.93%) • Memory: 46.63 MB A brilliant insight — redistribution is just a divisibility check! No complex simulation needed. #DSA #LeetCode #Java #HashMap #Strings #CodingJourney #ProblemSolving