Largest Submatrix With Rearrangements via Matrix Optimization

🚀 Day 21 of 100 Days LeetCode Challenge Problem: Flip Square Submatrix Vertically Day 21 brings a clean matrix manipulation problem—simple logic, but important for fundamentals 🔥 💡 Key Insight: We are given: Top-left corner (x, y) Size k 👉 We need to flip the k x k submatrix vertically → Meaning: reverse the order of rows inside that square 🔍 Core Approach: 1️⃣ Identify Submatrix Boundaries Rows: x → x + k - 1 Columns: y → y + k - 1 2️⃣ Swap Rows Vertically Swap: Row x ↔ Row x + k - 1 Row x + 1 ↔ Row x + k - 2 Continue until middle 👉 Only swap elements within column range [y, y + k - 1] 💡 Visualization: Top row ⬇️ becomes bottom Bottom row ⬆️ becomes top 🔥 What I Learned Today: Matrix problems often come down to index manipulation Clear boundary definition avoids mistakes Simple operations can still test precision 📈 Challenge Progress: Day 21/100 ✅ 3 Weeks Consistency Strong! 💪 LeetCode, Matrix Manipulation, Arrays, Simulation, Indexing, DSA Practice, Coding Challenge, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #Matrix #Arrays #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

🚀 Day 18 of 100 Days LeetCode Challenge Problem: Count Submatrices with Top-Left Element and Sum ≤ k Today’s problem is a clean application of 2D Prefix Sum (Cumulative Sum) 🔥 💡 Key Insight: All valid submatrices must: Start from the top-left corner (0,0) Extend to any cell (i, j) 👉 So instead of checking all submatrices, we just: Compute sum from (0,0) to (i,j) Check if it’s ≤ k 🔍 Core Approach: 1️⃣ Build Prefix Sum Matrix prefix[i][j] = sum of all elements from (0,0) to (i,j) 2️⃣ Iterate Through Grid For every (i, j): If prefix[i][j] ≤ k → count it ✅ 👉 That’s it! No need for complex nested submatrix checks 🚀 🔥 What I Learned Today: Constraints simplify problems → use them wisely 2D prefix sum reduces O(n⁴) → O(n²) Always check if the problem has a fixed starting point 📈 Challenge Progress: Day 18/100 ✅ Almost 20 days consistency! LeetCode, Prefix Sum, Matrix, 2D Arrays, Optimization, Algorithms, DSA Practice, Coding Challenge, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #PrefixSum #Matrix #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

🚀 Day 16 of 100 Days LeetCode Challenge Problem: Get Biggest Three Rhombus Sums in a Grid Today’s problem was a matrix + geometry + prefix sum optimization challenge 🔥 💡 Key Insight: A rhombus is basically a rotated square, and we only need the border sum, not the entire area. 👉 Brute force works, but it’s slow. So we optimize using diagonal prefix sums. 🔍 Core Approach: 1️⃣ Understand Rhombus Shape Defined by a center and a “radius” Four edges → top, right, bottom, left 2️⃣ Efficient Border Sum Use diagonal prefix sums to quickly calculate edges Avoid recomputing each cell repeatedly 3️⃣ Track Top 3 Unique Sums Use a set or priority structure Keep only the largest 3 distinct values 🔥 What I Learned Today: Geometry-based problems require visual thinking Prefix sums are powerful beyond simple arrays Optimization matters when dealing with nested loops 📈 Challenge Progress: Day 16/100 ✅ Still consistent, still growing! LeetCode, Matrix, Prefix Sum, Geometry, Optimization, Arrays, DSA Practice, Coding Challenge, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #Matrix #PrefixSum #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

🚀 Day 19 of 100 Days LeetCode Challenge Problem: Count Submatrices With Equal Frequency of X and Y Today’s problem was a solid combination of 2D Prefix Sum + Hashing concept 🔥 💡 Key Insight: We need submatrices that: Include the top-left cell (0,0) Have equal number of 'X' and 'Y' Contain at least one 'X' 👉 Trick: Convert the grid into values: 'X' → +1 'Y' → -1 '.' → 0 🔍 Core Approach: 1️⃣ 2D Prefix Sum Transformation Build prefix sum based on above conversion 2️⃣ Check Each Submatrix (0,0 → i,j) If sum == 0 → equal number of X and Y ✅ 3️⃣ Extra Condition: Ensure at least one 'X' exists 👉 Track X count separately using another prefix matrix 🔥 What I Learned Today: Transforming problems into numbers simplifies logic Prefix sums + condition checks = powerful combo Always handle extra constraints carefully 📈 Challenge Progress: Day 19/100 ✅ Almost hitting Day 20! LeetCode, Prefix Sum, Matrix, Hashing, Problem Transformation, Algorithms, DSA Practice, Coding Challenge, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #PrefixSum #Matrix #Hashing #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

🚀 Day 22 of 100 Days LeetCode Challenge Problem: Determine Whether Matrix Can Be Obtained By Rotation Day 22 is a classic matrix rotation + simulation problem 🔥 💡 Key Insight: We can rotate the matrix in 90° steps (up to 4 times): 90° 180° 270° 360° (back to original) 👉 If at any step mat == target → ✅ True 🔍 Core Approach: 1️⃣ Rotate Matrix (90° Clockwise) Transpose the matrix Reverse each row 👉 This gives one 90° rotation 2️⃣ Repeat Rotation 4 Times After each rotation: Compare with target 👉 If match found → return true 👉 Else after 4 rotations → false 💡 Optimization: Early exit when match is found Avoid unnecessary rotations 🔥 What I Learned Today: Matrix rotation is a standard pattern Simulation problems require step-by-step accuracy Reusing logic reduces complexity 📈 Challenge Progress: Day 22/100 ✅ Staying consistent & sharp! LeetCode, Matrix, Rotation, Simulation, Arrays, DSA Practice, Coding Challenge, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #Matrix #Rotation #Simulation #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

🚀 Day 14 — Max Consecutive Ones Continuing my journey of improving problem-solving skills with consistency and discipline — one problem every day. Today’s problem was about identifying patterns in sequences — simple logic, but very useful in many real-world scenarios. 🧩 Problem Solved: • Max Consecutive Ones (LeetCode #485) 📚 Topic: Arrays + Traversal 💡 Key Insight: We can track consecutive 1’s using a counter and reset it whenever we encounter a 0 — keeping track of the maximum along the way. ⚡ Approach: • Initialize count = 0 and max_count = 0 • Traverse the array • If element is 1 → increment count • Update max_count • If element is 0 → reset count to 0 • Return max_count 🎯 Takeaway: Tracking patterns during traversal is a powerful technique for solving sequence-based problems. ⏱ Complexity: • Time → O(n) • Space → O(1) 💻 Example: Input → [1,1,0,1,1,1] → Output → 3 Input → [1,0,1,1,0,1] → Output → 2 Small patterns reveal big insights 🚀 #ProblemSolving #LeetCode #Arrays #CodingJourney #100DaysOfCode #Consistency #LearningInPublic

Day 79 on LeetCode Smallest Index With Digit Sum Equal to Index 🔢✅ Keeping the streak going with a simple yet interesting digit manipulation + simulation problem 💯 🔹 Approach Used in My Solution The goal was to find the smallest index i such that the sum of digits of nums[i] equals i. Key idea: • Traverse the array from left to right • For each element, calculate the digit sum • Compare it with the current index • Return the first index where the condition satisfies • If none found → return -1 A clean and direct implementation without overcomplication. ⚡ Complexity: • Time Complexity: O(n * d) (d = number of digits) • Space Complexity: O(1) 💡 Key Takeaways: • Practiced digit extraction using modulo and division • Reinforced writing simple simulation-based solutions • Reminder: not every problem needs optimization — clarity matters 🔥 Consistency maintained, step by step progress continues. #LeetCode #DSA #Algorithms #DataStructures #Arrays #Math #Simulation #ProblemSolving #Coding #Programming #Cpp #STL #SoftwareEngineering #ComputerScience #CodingPractice #DeveloperLife #TechJourney #CodingDaily #Consistency #100DaysOfCode #BuildInPublic #AlgorithmPractice #CodingSkills #Developers #TechCommunity #SoftwareDeveloper #EngineeringJourney

🚀 Day 24 of 100 Days LeetCode Challenge Problem: Construct Product Matrix Today’s problem is a 2D extension of a classic concept: 👉 “Product of Array Except Self” 🔥 💡 Key Insight: For each cell (i, j), we need: Product of all elements except grid[i][j] Without using division (important!) 🔍 Core Approach: 1️⃣ Flatten the Matrix Treat the matrix like a 1D array 2️⃣ Prefix Product Store product of elements before index 3️⃣ Suffix Product Store product of elements after index 4️⃣ Final Value: p[i][j] = prefix * suffix % 12345 👉 This avoids division and works efficiently 💡 Optimization: Use modulo at every step to prevent overflow Space can be optimized by reusing arrays 🔥 What I Learned Today: Classic problems can appear in different forms (1D → 2D) Prefix & suffix patterns are extremely reusable Avoiding division is a common constraint in interviews 📈 Challenge Progress: Day 24/100 ✅ Almost 25 days strong! LeetCode, Prefix Product, Suffix Product, Matrix, Arrays, Optimization, Modular Arithmetic, DSA Practice, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #Matrix #PrefixSum #Optimization #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

🚀 Day 23 of 100 Days LeetCode Challenge Problem: Maximum Non-Negative Product in a Matrix Today’s problem was a deep dive into Dynamic Programming with edge cases (negative values) 🔥 💡 Key Insight: Since the grid contains negative numbers, the product can flip sign. 👉 So at each cell, we must track: Maximum product so far Minimum product so far Because: Negative × Negative = Positive 💥 🔍 Core Approach (DP): 1️⃣ DP State: For each cell (i, j) maintain: maxProduct[i][j] minProduct[i][j] 2️⃣ Transition: From top (i-1, j) and left (i, j-1): Multiply current value with both max & min Take: max → for maxProduct min → for minProduct 3️⃣ Final Answer: If final max ≥ 0 → return max % (10⁹ + 7) Else → return -1 🔥 What I Learned Today: Negative values require tracking both extremes DP is not always just “max”—sometimes it’s min + max together Edge cases define the real difficulty of a problem 📈 Challenge Progress: Day 23/100 ✅ Getting stronger with DP! LeetCode, Dynamic Programming, Matrix, Optimization, Negative Numbers, Algorithms, DSA Practice, Coding Challenge, Problem Solving #100DaysOfCode #LeetCode #DSA #CodingChallenge #DynamicProgramming #Matrix #ProblemSolving #TechJourney #ProgrammerLife #SoftwareDeveloper #CodingLife #LearnToCode #Developers #Consistency #GrowthMindset #InterviewPrep

🚀 Day 6 — Remove Duplicates from Sorted Array Continuing my journey of improving problem-solving skills with consistency and discipline — one problem every day. Today’s problem focused on optimizing space and modifying arrays efficiently in-place. 🧩 Problem Solved: • Remove Duplicates from Sorted Array (LeetCode #26) 📚 Topic: Two Pointers + Array Manipulation 💡 Key Insight: Since the array is already sorted, duplicates are adjacent — making it possible to remove them using a two-pointer approach without extra space. ⚡ Approach: • Initialize a pointer i to track unique elements • Traverse array using another pointer j • Compare nums[j] with nums[i] • If different → move i forward and update value • Return i + 1 as the count of unique elements 🎯 Takeaway: Understanding problem constraints (like sorted input) can lead to more efficient and elegant solutions. ⏱ Complexity: • Time → O(n) • Space → O(1) 💻 Example: Input → [1, 1, 2] Output → 2 (Array becomes [1, 2, _]) Input → [0,0,1,1,1,2,2,3,3,4] Output → 5 (Array becomes [0,1,2,3,4,_,_,_,_,_]) Efficiency isn’t always about doing more — sometimes it’s about doing less, smarter 🚀 #ProblemSolving #LeetCode #TwoPointers #CodingJourney #100DaysOfCode #Consistency #LearningInPublic