Letter Combinations of a Phone Number LeetCode Challenge

✅ 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 31 of 100 Days LeetCode Challenge Problem: 🔹 #130 – Surrounded Regions 🔗 https://lnkd.in/gzziasbj Learning Journey: 🔹 Today’s problem focused on identifying and capturing regions in a 2D board that are fully surrounded. 🔹 I used graph traversal to explore connected regions of 'O' cells. 🔹 For each region, I tracked whether it touches the boundary of the board. 🔹 Only regions completely enclosed by 'X' were flipped, while boundary-connected regions were preserved. Concepts Used: 🔹 Breadth-First Search (BFS) 🔹 Graph Traversal 🔹 Matrix Traversal 🔹 Connected Components Key Insight: 🔹 Boundary-connected regions should never be captured. 🔹 Tracking region connectivity is essential to determine whether a region is surrounded. 🔹 Grid problems often reduce cleanly to graph traversal with careful boundary handling. #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 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 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 40 of 100 Days LeetCode Challenge Problem: 🔹 #1200 – Minimum Absolute Difference 🔗 https://lnkd.in/gdXZxeGh Learning Journey: 🔹 Today’s problem focused on finding all pairs of elements with the minimum absolute difference in an array. 🔹 I first sorted the array so that the smallest differences would appear between adjacent elements. 🔹 By scanning the sorted list once, I tracked the minimum difference and collected all valid pairs. 🔹 This approach avoids unnecessary comparisons and improves efficiency. Concepts Used: 🔹 Sorting 🔹 Greedy Scanning 🔹 Array Traversal 🔹 Optimization Key Insight: 🔹 Sorting simplifies many comparison-based problems. 🔹 Minimum differences in a sorted array will always occur between neighboring elements. 🔹 Maintaining a running minimum helps build the result efficiently in one pass. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 28 of 100 Days LeetCode Challenge Problem: 🔹 #133 – Clone Graph 🔗 https://lnkd.in/gsciP4qv Learning Journey: 🔹 Today’s problem focused on creating a deep copy of a connected graph. 🔹 I used Depth-First Search (DFS) to traverse the graph and clone each node. 🔹 A hashmap stores the mapping between original nodes and their cloned counterparts to avoid duplicate copies. 🔹 This approach also handles cycles gracefully by returning already-cloned nodes when revisited. Concepts Used: 🔹 Depth-First Search (DFS) 🔹 Graph Traversal 🔹 Hash Map 🔹 Deep Copy Key Insight: 🔹 Graph cloning requires tracking visited nodes to prevent infinite loops. 🔹 DFS provides a clean recursive way to clone nodes and their neighbors. 🔹 Maintaining a reference map is essential for handling cyclic graphs correctly. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 38 of 100 Days LeetCode Challenge Problem: 🔹 #323 – Number of Connected Components in an Undirected Graph 🔗 https://lnkd.in/gRVWsWgZ Learning Journey: 🔹 Today’s problem focused on counting connected components in an undirected graph. 🔹 I represented the graph using an adjacency list built from the edge list. 🔹 Using Depth-First Search (DFS), I explored all nodes reachable from a starting node. 🔹 Each new DFS traversal from an unvisited node indicates a new connected component. Concepts Used: 🔹 Depth-First Search (DFS) 🔹 Graph Representation (Adjacency List) 🔹 Connected Components 🔹 Graph Traversal Key Insight: 🔹 Graph problems often reduce to exploring connectivity between nodes. 🔹 Tracking visited nodes prevents redundant traversals. 🔹 Iterative DFS using a stack provides a clean and efficient solution. #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