Surrounded Regions LeetCode Challenge

✅ Day 51 of 100 Days LeetCode Challenge Problem: 🔹 #973 – K Closest Points to Origin 🔗 https://lnkd.in/gzp_xraa Learning Journey: 🔹 Today’s problem focused on finding the k points closest to the origin in a 2D plane. 🔹 I calculated the squared Euclidean distance for each point to avoid unnecessary square root operations. 🔹 Using a min-heap, I efficiently retrieved the smallest distances. 🔹 A hashmap helped group points with the same distance, ensuring correct retrieval of coordinates. Concepts Used: 🔹 Heap / Priority Queue 🔹 Euclidean Distance 🔹 Hash Map 🔹 Greedy Selection Key Insight: 🔹 Squared distance is sufficient for comparison and avoids extra computation. 🔹 Heaps are ideal for efficiently extracting the smallest (or largest) k elements. 🔹 Choosing the right data structure significantly simplifies implementation. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 43 of 100 Days LeetCode Challenge Problem: 🔹 #684 – Redundant Connection 🔗 https://lnkd.in/gWtKJ-FA Learning Journey: 🔹 Today’s problem focused on detecting an extra edge that creates a cycle in an undirected graph. 🔹 I used the Union-Find (Disjoint Set Union) data structure to track connected components. 🔹 For each edge, I checked whether both nodes already belong to the same set. 🔹 If they do, adding that edge forms a cycle, making it the redundant connection. Concepts Used: 🔹 Union-Find (Disjoint Set) 🔹 Path Compression 🔹 Graph Cycle Detection 🔹 Connected Components Key Insight: 🔹 Union-Find provides an efficient way to detect cycles during edge additions. 🔹 Path compression optimizes repeated parent lookups. 🔹 Incrementally building connectivity helps quickly identify redundant edges. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 44 of 100 Days LeetCode Challenge Problem: 🔹 #3713 – Longest Balanced Substring 🔗 https://lnkd.in/gfryNgam Learning Journey: 🔹 Today’s problem focused on finding the longest substring where all characters appear with equal frequency. 🔹 I explored all possible substrings by fixing a starting index and expanding the window step by step. 🔹 A frequency array helped track character counts along with the number of distinct characters and maximum frequency. 🔹 By validating whether all active characters share the same count, I identified balanced substrings efficiently. Concepts Used: 🔹 String Processing 🔹 Frequency Counting 🔹 Nested Traversal 🔹 Sliding Window Concepts Key Insight: 🔹 Balanced substring problems rely on maintaining strict frequency conditions. 🔹 Tracking distinct characters and maximum frequency simplifies validation logic. 🔹 Smart bookkeeping can make brute-force approaches effective for constrained problems. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 34 of 100 Days LeetCode Challenge Problem: 🔹 #38 – Count and Say 🔗 https://lnkd.in/gZKE3maw Learning Journey: 🔹 Today’s problem focused on generating the nth term of the Count and Say sequence. 🔹 Each term is built by reading the previous term and describing consecutive digits using Run-Length Encoding (RLE). 🔹 I iteratively generated each sequence starting from "1" until reaching the desired term. 🔹 A helper function handles counting consecutive characters and forming the next sequence. Concepts Used: 🔹 String Manipulation 🔹 Run-Length Encoding (RLE) 🔹 Iterative Simulation 🔹 Pattern Recognition Key Insight: 🔹 Many sequence problems rely on recognizing and encoding patterns. 🔹 Breaking the logic into a helper function improves readability and correctness. 🔹 Iterative construction avoids unnecessary recursion and keeps the solution efficient. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 35 of 100 Days LeetCode Challenge Problem: 🔹 #62 – Unique Paths 🔗 https://lnkd.in/gx2ZcaVk Learning Journey: 🔹 Today’s problem focused on counting the number of unique paths in a grid from the top-left to the bottom-right corner. 🔹 Instead of using Dynamic Programming, I applied a mathematical combinatorics approach. 🔹 The problem reduces to choosing positions for moves (right and down) in a fixed sequence. 🔹 Using combinations provides a clean and optimal solution with constant space. Concepts Used: 🔹 Combinatorics 🔹 Mathematical Optimization 🔹 Problem Reduction 🔹 Grid Path Counting Key Insight: 🔹 Grid path problems often have a direct combinatorial interpretation. 🔹 Recognizing the fixed number of moves simplifies the problem significantly. 🔹 Mathematical solutions can be more elegant and efficient than DP in certain cases. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 39 of 100 Days LeetCode Challenge Problem: 🔹 #114 – Flatten Binary Tree to Linked List 🔗 https://lnkd.in/g6xn2K3g Learning Journey: 🔹 Today’s problem focused on transforming a binary tree into a flattened linked list in-place. 🔹 I used an iterative approach, modifying pointers while traversing the tree. 🔹 For each node with a left subtree, I found the rightmost node of that subtree and connected it to the current node’s right subtree. 🔹 Then, I moved the left subtree to the right and continued traversal. Concepts Used: 🔹 Binary Trees 🔹 Tree Traversal 🔹 Pointer Manipulation 🔹 In-place Modification Key Insight: 🔹 Tree restructuring problems often rely on careful pointer adjustments. 🔹 Finding the predecessor (rightmost node of left subtree) helps preserve traversal order. 🔹 Iterative solutions can avoid recursion and reduce extra space usage. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 58 of 100 Days LeetCode Challenge Problem: 🔹 #1680 – Concatenation of Consecutive Binary Numbers 🔗 https://lnkd.in/gt22hnfF Learning Journey: 🔹 Today’s problem involved concatenating the binary representations of numbers from 1 to n. 🔹 I generated binary strings using bin(i)[2:] and appended them sequentially. 🔹 After forming the final binary string, I converted it back to an integer. 🔹 Since the result can be very large, I applied modulo 10**9+7. Concepts Used: 🔹 Binary Representation 🔹 String Manipulation 🔹 Modular Arithmetic 🔹 Simulation Key Insight: 🔹 Direct string concatenation works but is not optimal for large n. 🔹 Efficient solutions avoid large intermediate strings by using bit shifts and modular arithmetic at each step. 🔹 Understanding bit-length growth is crucial for optimization in binary construction problems. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 46 of 100 Days LeetCode Challenge Problem: 🔹 #91 – Decode Ways 🔗 https://lnkd.in/gpZQshBr Learning Journey: 🔹 Today’s problem focused on counting the number of ways to decode a numeric string into letters. 🔹 I used a Dynamic Programming approach with space optimization, tracking only the previous two states. 🔹 At each step, I checked both single-digit and two-digit decoding possibilities. 🔹 Careful handling of edge cases like leading zeros was essential to ensure valid decoding paths. Concepts Used: 🔹 Dynamic Programming 🔹 Space Optimization 🔹 String Parsing 🔹 State Transition Key Insight: 🔹 Many decoding problems depend on evaluating valid transitions from previous states. 🔹 Maintaining only necessary previous results reduces space complexity to O(1). 🔹 Edge cases involving zeros are critical in avoiding invalid combinations. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 52 of 100 Days LeetCode Challenge Problem: 🔹 #215 – Kth Largest Element in an Array 🔗 https://lnkd.in/gjgHCqqA Learning Journey: 🔹 Today’s problem focused on finding the kth largest element in an unsorted array. 🔹 I converted the problem into a max-heap scenario by negating all elements and using Python’s min-heap. 🔹 After heapifying the array, I popped elements k-1 times to reach the kth largest value. 🔹 Finally, I negated the result to restore the original value. Concepts Used: 🔹 Heap / Priority Queue 🔹 Max-Heap Simulation 🔹 Array Transformation 🔹 Selection Algorithms Key Insight: 🔹 Converting values allows efficient simulation of a max-heap using a min-heap. 🔹 Heap operations ensure O(n + k log n) complexity. 🔹 Selection problems often become simpler with priority queue structures. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 57 of 100 Days LeetCode Challenge Problem: 🔹 #1404 – Number of Steps to Reduce a Number in Binary Representation to One 🔗 https://lnkd.in/ggb5GXaW Learning Journey: 🔹 Today’s problem focused on reducing a binary number to 1 using specific rules. 🔹 If the number is even, divide it by 2. If it is odd, add 1. 🔹 I converted the binary string to an integer, applied the operation, and converted it back to binary after each step. 🔹 The process continued until the value became "1", counting the total operations. Concepts Used: 🔹 Binary Representation 🔹 Bit Manipulation Concepts 🔹 Simulation 🔹 Conditional Logic Key Insight: 🔹 Binary problems often map directly to parity checks (even vs odd). 🔹 Simulation is straightforward but understanding bit behavior can lead to optimized solutions. 🔹 Recognizing patterns in binary transitions improves problem-solving efficiency. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity