LeetCode Challenge Day 12: Subsets Generation with Backtracking

✅ Day 14 of 100 Days LeetCode Challenge Problem: 🔹 #39 – Combination Sum 🔗 https://lnkd.in/gZc8SUvr Learning Journey: 🔹 Today’s problem focused on finding all unique combinations of numbers that sum up to a given target. 🔹 I solved it using backtracking, where at each step I had two choices: include the current number or move to the next candidate. 🔹 Unlike subset problems, the same element can be reused multiple times, so the recursive call stays on the same index when including an element. 🔹 The recursion stops when the total exceeds the target or when a valid combination is found. Concepts Used: 🔹 Backtracking 🔹 Recursion 🔹 Depth-First Search (DFS) 🔹 Pruning Recursive Paths Key Insight: 🔹 Backtracking is especially powerful for constraint-based problems like sum and combination generation. 🔹 Pruning paths early (when the sum exceeds the target) significantly improves efficiency. 🔹 Understanding how index movement controls reuse of elements is key to mastering combination problems. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 15 of 100 Days LeetCode Challenge Problem: 🔹 #40 – Combination Sum II 🔗 https://lnkd.in/g-w7rAcg Learning Journey: 🔹 Today’s problem was an extension of yesterday’s Combination Sum, but with an added constraint: each number can be used only once, and the input may contain duplicates. 🔹 I solved it using backtracking combined with sorting to group duplicate values together. 🔹 At each recursion level, I iterated through the candidates and skipped duplicate elements at the same level to avoid generating repeated combinations. 🔹 The recursion moves to the next index after choosing a number, ensuring elements are not reused. Concepts Used: 🔹 Backtracking 🔹 Recursion 🔹 Depth-First Search (DFS) 🔹 Handling Duplicates 🔹 Pruning Recursive Paths Key Insight: 🔹 Sorting is crucial when dealing with duplicate candidates in combination problems. 🔹 Skipping duplicates at the same recursion level prevents repeated combinations without missing valid ones. 🔹 Small changes in index movement can completely change problem constraints and solution behavior. #LeetCode #DataStructures #Algorithms #CodingInterview #SoftwareEngineering #SoftwareDeveloper #ProblemSolving #Programming #ComputerScience #TechCareers #100DaysOfCode #DailyCoding #Consistency #LearningInPublic #Python #BackendDevelopment #InterviewPreparation #TechCommunity

✅ Day 13 of 100 Days LeetCode Challenge Problem: 🔹 #90 – Subsets II 🔗 https://lnkd.in/gCyD9UNb Learning Journey: 🔹 Today’s problem was similar to yesterday’s (#78 – Subsets), but this time the array could contain duplicates, so we had to ensure the solution set did not contain duplicate subsets. 🔹 I approached it using backtracking, again making a binary decision at each index: include or exclude the current element. 🔹 To handle duplicates, I sorted the array first and skipped duplicate elements at the same recursion level, preventing repeated subsets. 🔹 Copying the current solution at each step preserves the subset before backtracking continues. Concepts Used: 🔹 Backtracking 🔹 Recursion 🔹 Depth-First Search (DFS) 🔹 Handling Duplicates Key Insight: 🔹 Sorting and carefully skipping duplicates is essential when generating unique subsets. 🔹 Subset problems map naturally to an include/exclude decision tree. 🔹 Backtracking remains a clean way to explore all combinations, even with duplicate elements. #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 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 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 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 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 16 of 100 Days LeetCode Challenge Problem: 🔹 #79 – Word Search 🔗 https://lnkd.in/gHeRzA2d Learning Journey: 🔹 Today’s problem shifted from combination generation to grid-based search using DFS. 🔹 The goal was to check whether a given word exists in a 2D board by moving horizontally or vertically between adjacent cells. 🔹 I used Depth-First Search (DFS) with backtracking, starting from each cell that matched the first character of the word. 🔹 To avoid revisiting the same cell in a single path, I temporarily marked the cell as visited and restored it after exploring all directions. Concepts Used: 🔹 Depth-First Search (DFS) 🔹 Backtracking 🔹 Matrix Traversal 🔹 Recursive Search Key Insight: 🔹 Backtracking is not limited to combinatorial problems; it is equally effective for grid traversal and path search problems. 🔹 Marking and restoring visited cells is essential to correctly explore all possible paths. 🔹 Careful boundary checks and base conditions are critical for correctness in recursive grid problems. #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