"Deep Copying Linked Lists with Random Pointers on LeetCode"

🔹 Day 71 of #100DaysOfLeetCodeChallenge 🔹 🚀 Problem: Letter Combinations of a Phone Number 🔑 Topic: Backtracking 🧠 Approach: This problem converts digits (2–9) into possible letter combinations like an old phone keypad. Here’s the step-by-step logic 👇 Use a mapping array to represent letters for each digit. Apply recursion + backtracking to explore all letter combinations. At each step, append a character, move to the next digit, and then backtrack by removing the last character. ⏳ Time Complexity: O(4ⁿ) — each digit can map to up to 4 letters 💾 Space Complexity: O(n) — recursion stack and temporary string builder 📌 Example: Input: digits = "23" Output: ["ad","ae","af","bd","be","bf","cd","ce","cf"] ✅ 🎯 Takeaway: A perfect example of how backtracking efficiently explores all possible combinations through recursive branching. 🌿 #LeetCode #DSA #Backtracking #Recursion #ProblemSolving #100DaysOfLeetCodeChallenge 🚀

💡 𝐋𝐞𝐞𝐭𝐂𝐨𝐝𝐞 𝐃𝐚𝐢𝐥𝐲 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 -𝟑𝟐𝟏𝟕. 𝐃𝐞𝐥𝐞𝐭𝐞 𝐍𝐨𝐝𝐞𝐬 𝐅𝐫𝐨𝐦 𝐋𝐢𝐧𝐤𝐞𝐝 𝐋𝐢𝐬𝐭 𝐏𝐫𝐞𝐬𝐞𝐧𝐭 𝐢𝐧 𝐀𝐫𝐫𝐚𝐲 🧩 Problem Summary: We are given a linked list and an array nums. The goal is to remove all nodes from the linked list whose values appear in nums, and then return the modified linked list. 🧠 Approach : • Store all elements from nums in an 𝐮𝐧𝐨𝐫𝐝𝐞𝐫𝐞𝐝_𝐬𝐞𝐭 for O(1) lookup. • Handle deletions from the beginning of the list (in case the head node’s value exists in nums). • Traverse the linked list and skip nodes whose values are present in the set. • Return the modified head of the list. 💨 Time Complexity: O(N + M) (where N = number of nodes in list, M = size of nums) 💾 Space Complexity: O(M) 🧩 Key Learning: • Efficient node deletion from a linked list becomes simpler when combined with hashing. • Using an unordered_set helps in quick membership checking and clean logic. #LeetCode #CodingChallenge #Leetcode #DataStructures #LinkedList #DSA #ProblemSolving #100DaysOfCode

🚀 Day 98 of My LeetCode Journey — Problem 19: Remove Nth Node From End of List 💡 Problem Insight: Today’s problem was about removing the n-th node from the end of a singly linked list. It’s a clean yet tricky problem that tests your understanding of linked list traversal, pointers, and edge case handling. 🧠 Concept Highlight: The most elegant solution uses the two-pointer technique: Move the fast pointer n steps ahead first. Then move both fast and slow pointers one step at a time until the fast pointer reaches the end. The slow pointer will be right before the node to delete. This ensures a single-pass (O(n)) solution — optimal and precise. 💪 Key Takeaway: It’s not always about rushing to the end — sometimes, starting with the right gap makes the journey efficient and smooth. ✨ Daily Reflection: Linked list problems continue to refine my logical precision and strengthen my foundation for advanced data structures. #Day98 #LeetCode #100DaysOfCode #LinkedList #TwoPointerTechnique #ProblemSolving #DSA #CodingJourney #LearnByDoing #SoftwareEngineering

🚀LeetCode Daily Challenge 🧩 Problem: Delete Nodes From Linked List Present in Array Problem Intuition: Given a linked list and an array of integers, you need to remove all nodes from the linked list whose values are present in the given array. In simple terms, delete every node that matches any number in the array and return the updated linked list. 💡Example Insight: Let’s say: nums = [1, 2, 3] Linked List = 1 → 2 → 4 → 3 → 5 After removing nodes with values 1, 2, and 3, the linked list becomes: 4 → 5 🧠 Approach & Strategy: ✔ Store all numbers from the array nums into an unordered_set for quick lookup (O(1) average). ✔ Traverse the linked list, and for each node: Skip it if its value is present in the set. Otherwise, add it to the new linked list. ✔ Finally, return the head of this new linked list. ⚙️ Complexity Analysis: Time Complexity: O(n + m) → n = length of linked list, m = size of array. Space Complexity: O(m) → For storing array elements in a set. 🔗 Problem: https://lnkd.in/dWA2hsDr 💻 Solution: https://lnkd.in/dypBvguK #LeetCode #DSA #Cpp #ProblemSolving #CodingChallenge #LeetCodeDailyChallenge

✅ Day 4/75 🌟 Today’s Progress 1️⃣ Longest Consecutive Sequence — LeetCode Medium Problem: Given an unsorted array of integers, return the length of the longest consecutive elements sequence. You must write an algorithm that runs in O(n) time. 🔹Approaches: 1️⃣ Sorting Approach (Brute Force) Sorted the array and count the consecutive elements. Time Complexity: O(N log N). 2️⃣ Optimal – HashSet Stored all the numbers in a HashSet. For each number, checked if it’s the start of a sequence (i.e., num - 1 not in set). Then counted how long the consecutive sequence continues. ✅ Time: O(N) | Space: O(N) 2️⃣ Product of Array Except Self — LeetCode Medium Problem: Given an array nums, return an array answer such that answer[i] equals the product of all elements except nums[i], without using division, in O(n) time. 🔹Approaches: 1️⃣ Brute Force: Multiplied all elements except self for each index. ⏱️ Time: O(N²) 2️⃣ Optimal – Prefix & Suffix Product First pass: calculated the prefix products (product of all elements to the left). Second pass: multiplied each element by the suffix product (product of all elements to the right). ✅ Time: O(N) | Space: O(1) (excluding output array) On to Day 5 tomorrow! ✨ #NeetCode #Blind75 #DSA #LeetCode #CodingChallenge #ProblemSolving

🔗 Day 75 of #100DaysOfCode 🔗 🌳 Problem: Binary Tree Postorder Traversal – LeetCode ✨ Approach: Implemented a recursive depth-first traversal that processes the left subtree, then right subtree, and finally the root node — perfectly matching the postorder pattern (Left → Right → Root). The solution is clean, intuitive, and highlights the elegance of recursion in tree traversal! 🌿 📊 Complexity Analysis: ⏱ Time Complexity: O(n) — each node is visited exactly once 💾 Space Complexity: O(n) — recursion stack in the worst case (skewed tree) ✅ Runtime: 0 ms (Beats 100% 🚀) ✅ Memory: 43.07 MB 💡 Key Insight: Recursion beautifully mirrors the natural hierarchy of trees — by trusting the call stack, we achieve simplicity and clarity in solving even complex traversal problems. 🌱 #LeetCode #100DaysOfCode #ProblemSolving #DSA #BinaryTree #Recursion #AlgorithmDesign #CodeJourney #ProgrammingChallenge #LogicBuilding #Efficiency #CodingDaily

🧩 LeetCode Challenge – Day 73 ✅ Worked on a linked list problem today — clean logic, but plenty of room for optimization. 🔗 LeetCode 3217 – Delete Nodes From Linked List Present in Array The goal was to remove nodes whose values appear in a given array. Instead of using hashing for lookups, I applied binary search after sorting the reference array — keeping the approach elegant and efficient. It was a great reminder that data structure choice can completely change a problem’s flow and clarity. 💡 Key Takeaways: • Binary search isn’t just for arrays — it enhances linked list problems too. • Efficiency through structure — sorted data can replace extra space usage. • Exploring alternatives deepens understanding far beyond standard templates. #Day73 #LeetCodeChallenge #100DaysOfCode #DSA #CodingJourney #ProblemSolving #LinkedList #BinarySearch #Pointers #DataStructures

📌 Day 39/150 – Rotate List (LeetCode #61) Today’s problem was a brilliant exploration of how subtle linked list operations can completely change the shape of a data structure! 🔁✨ The task? Given a linked list, rotate it to the right by k positions. Instead of shifting values, we must carefully adjust the links — no cheating with arrays! 😄 This problem reinforces how pointer manipulation and structural thinking work hand-in-hand in linked list questions. 🧠 🔹 Brute Force Idea A naive thought would be: 👉 Rotate one step at a time 👉 Move the last node to the front Repeat this k times. ✅ Easy to visualize ❌ Too slow (k rotations × n operations = inefficient!) ❌ Not scalable for large k 🔹 Optimal Approach – Smart Pointer Manipulation The elegant approach lies in understanding patterns: 👉 First, compute the length of the list. 👉 Connect the tail to the head — forming a temporary circle! 🔄 👉 Reduce k using modulo (k = k % length) 👉 Traverse to the correct breaking point. 👉 Break the circle to form the rotated list. You handle: 🔸 Circular linked list logic 🔸 Tail–head reattachment 🔸 Precise pointer breaking Very clean, very efficient! ✨ 🧠 Example Visualization Input: 1 → 2 → 3 → 4 → 5, k = 2 After rotation: 4 → 5 → 1 → 2 → 3 Only the links change — the magic of pointers! 🔧 ⏱️ Time & Space Complexity ComplexityValueTimeO(n) — just one traversalSpaceO(1) — done in-place 💡 Key Learning: This problem helps build confidence in: ✅ Recognizing patterns ✅ Using circular logic ✅ Efficient pointer manipulation ✅ Avoiding unnecessary extra space It’s one of those linked list questions that feels intimidating at first, but becomes satisfying once you see the strategy. Solving this opens the door to related problems like: 📍 Rotate Array 📍 Reverse Nodes in K-Group 📍 Swap Nodes in Pairs Linked lists may bend… but they don't break your confidence anymore. 💪😄 #150DaysOfCode #LeetCode #RotateList #LinkedLists #Pointers #DSA #CodingChallenge #SoftwareEngineering #LearningJourney #ProblemSolving 🚀🔥

🚀 Day 61 | Recursion & Balanced BST Construction Today’s problem focused on building a height-balanced Binary Search Tree from a sorted array — a perfect use case for divide-and-conquer. 🧩 Problem Solved: 108. Convert Sorted Array to Binary Search Tree • Approach: Used recursion — picked the middle element as the root, recursively built left and right subtrees from the halves. • Insight: Balanced trees naturally emerge when you divide sorted data around the midpoint — a great illustration of symmetry in recursion. ✨ Key Takeaway: Recursion mirrors structure — when you trust the process, complex problems unfold with simple, elegant logic. 📚 Topics: Binary Search Tree · Recursion · Divide and Conquer 💻 Platform: LeetCode #DSA #LeetCode #ProblemSolving #DailyCoding #Recursion #BinarySearchTree #Consistency

There are a bunch of hard problems on LeetCode that use basic graph traversal, which is pretty straightforward. However, they might be a bit more complex because we need to create, or identify how to create, a graph representation. The post: https://lnkd.in/dtQCR26x The problem: https://lnkd.in/dEfwjQPN #LeetCode #DSATips #DSA #ThinkDSA #ProblemSolving