Remove Duplicates from Sorted Array II LeetCode Challenge

🚀 50 Important Coding Questions – Question 2/50 🔹 Rotate Array | LeetCode (Medium) Another classic interview problem that tests your array manipulation & in-place logic 👇 📌 Problem Statement Given an integer array nums, rotate the array to the right by k steps, where k is non-negative. 💡 Optimized Approach (Reverse Technique) Instead of rotating one-by-one, use 3 reversals: 1️⃣ Reverse the entire array 2️⃣ Reverse the first k elements 3️⃣ Reverse the remaining elements ⏱ Time Complexity: O(n) 📦 Space Complexity: O(1) (In-place) ✅ Why this problem is important? ✔ Teaches in-place array manipulation ✔ Avoids extra memory usage ✔ Frequently asked in FAANG interviews ✔ Builds intuition for rotation & reversal logic 📌 LeetCode Result: ✔ Accepted ⚡ Runtime: 0 ms (Beats 100%) 📊 Memory Efficient 🔔 This is Question 2 of my “50 Important Coding Questions” series. Follow for daily DSA problems, optimized solutions, and interview-ready logic 💻✨ 👉 Question 3 coming soon… #DSA #LeetCode #RotateArray #CPlusPlus #CodingInterview #Arrays #ProblemSolving #50ImportantQuestions #TopInterview150

𝗟𝗲𝗲𝘁𝗖𝗼𝗱𝗲 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 – 𝗠𝗮𝘀𝘁𝗲𝗿 𝗖𝗼𝗱𝗶𝗻𝗴 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 𝘄𝗶𝘁𝗵 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀 Boost your problem-solving skills with essential LeetCode questions every developer should practice. This guide covers popular coding problems from arrays, strings, linked lists, stacks, queues, trees, graphs, recursion, and dynamic programming. Perfect for developers preparing for technical interviews at top tech companies. Improve your logic, coding speed, and confidence by practicing real interview-level problems with structured learning. #LeetCode #CodingInterview #DSA #ProblemSolving #SoftwareEngineering #ProgrammingPractice #TechInterviews #Developers #Algorithms #DataStructures #InterviewPreparation #CodeWithGandhi

🚀 50 Important Coding Questions – Question 17/50 🔹 Longest Substring Without Repeating Characters | LeetCode (Medium) A core Sliding Window problem that every coding interview candidate must master 👇 📌 Problem Statement Given a string s, find the length of the longest substring without repeating characters. 💡 Optimized Approach (Sliding Window + Hash Set / Map) 1️⃣ Use two pointers → left and right 2️⃣ Expand window while characters are unique 3️⃣ If duplicate found → move left until unique 4️⃣ Track maximum length ⏱ Time Complexity: O(n) 📦 Space Complexity: O(k) (character set size) ✅ Why this problem is important? ✔ Teaches Sliding Window mastery ✔ Improves substring handling logic ✔ Very common in FAANG interviews ✔ Foundation for many string problems 📌 LeetCode Result: ✔ Accepted ⚡ Efficient sliding window solution 🔔 This is Question 17 of my “50 Important Coding Questions” series. Keep coding daily — results will follow 💪 👉 Question 18 coming soon… #DSA #LeetCode #SlidingWindow #LongestSubstring #Strings #CPlusPlus #CodingInterview #ProblemSolving #50ImportantQuestions

🚀 50 Important Coding Questions – Question 1/50 🔹 Two Sum | LeetCode (Easy) If you’re starting your DSA / Coding Interview preparation, this problem is a must-know 👇 📌 Problem Statement Given an array of integers and a target, return the indices of two numbers such that they add up to the target. 💡 Optimized Approach Use Hash Map (unordered_map) Store element → index For each element, check if (target − current) already exists ⏱ Time Complexity: O(n) 📦 Space Complexity: O(n) ✅ Why this problem is important? ✔ Introduces Hashing ✔ Frequently asked in interviews ✔ Foundation for many advanced problems 📌 LeetCode Result: ✔ Accepted | Efficient Runtime | Optimized Solution 🔔 This is Question 1 of my “50 Important Coding Questions” series. Follow for daily DSA problems, clean code, and interview insights 💻✨ 👉 Next Question coming soon… #DSA #LeetCode #CodingInterview #TwoSum #CPlusPlus #ProblemSolving #HashMap #50DaysOfCode #LearnToCode

🚀 50 Important Coding Questions – Question 14/50 🔹 Longest Palindromic Substring | LeetCode (Medium) A classic String + Two Pointers (Expand Around Center) problem that builds deep understanding of palindrome logic 👇 📌 Problem Statement Given a string s, return the longest palindromic substring in s. 💡 Optimized Approach (Expand Around Center) Every character can be a palindrome center Check both: 👉 Odd-length palindrome 👉 Even-length palindrome Expand while characters match ⏱ Time Complexity: O(n²) 📦 Space Complexity: O(1) ✅ Why this problem is important? ✔ Strengthens palindrome intuition ✔ Teaches expand-around-center technique ✔ Frequently asked in interviews ✔ Foundation for advanced DP palindrome problems 📌 LeetCode Result: ✔ Accepted ⚡ Efficient & interview-ready approach 🔔 This is Question 14 of my “50 Important Coding Questions” series. Stay consistent — success is coming 💪 👉 Question 15 coming soon… #DSA #LeetCode #LongestPalindromicSubstring #Strings #TwoPointers #CPlusPlus #CodingInterview #ProblemSolving #50ImportantQuestions

🚀 50 Important Coding Questions – Question 6/50 🔹 Subarray Sum Equals K | LeetCode (Medium) A powerful combination of Prefix Sum + Hash Map that appears very frequently in coding interviews 👇 📌 Problem Statement Given an integer array nums and an integer k, return the total number of continuous subarrays whose sum equals k. 💡 Optimized Approach (Prefix Sum + Hashing) Maintain a running prefix sum For each index, check if 👉 (currentPrefixSum − k) exists in the map Count how many times it has appeared ⏱ Time Complexity: O(n) 📦 Space Complexity: O(n) ✅ Why this problem is important? ✔ Classic example of Prefix Sum with Hash Map ✔ Works even with negative numbers ✔ Asked frequently in FAANG & product-based interviews ✔ Builds intuition for subarray counting problems 📌 LeetCode Result: ✔ Accepted ⚡ Optimized & interview-ready solution 🔔 This is Question 6 of my “50 Important Coding Questions” series. Follow for daily DSA problems, optimized approaches, and clean C++ solutions 💻✨ 👉 Question 7 coming soon… #DSA #LeetCode #SubarraySumEqualsK #PrefixSum #HashMap #CPlusPlus #CodingInterview #50ImportantQuestions

🚀 50 Important Coding Questions – Question 9/50 🔹 Find First and Last Position of Element in Sorted Array | LeetCode (Medium) A classic Binary Search variation that tests how well you understand search boundaries 👇 📌 Problem Statement Given a sorted array of integers and a target value, find the starting and ending position of the target. If the target is not found, return [-1, -1]. 💡 Optimized Approach (Modified Binary Search) Use binary search twice First pass → find the first occurrence Second pass → find the last occurrence Narrow search space even after finding the target ⏱ Time Complexity: O(log n) 📦 Space Complexity: O(1) ✅ Why this problem is important? ✔ Strengthens binary search mastery ✔ Introduces boundary-based searching ✔ Very common in FAANG & product-based interviews ✔ Foundation for lower/upper bound problems 📌 LeetCode Result: ✔ Accepted ⚡ Runtime: 0 ms (Beats 100%) 📊 Memory Efficient 🔔 This is Question 9 of my “50 Important Coding Questions” series. Follow for daily DSA problems, optimized approaches, and interview-ready logic 💻✨ 👉 Question 10 coming soon… #DSA #LeetCode #BinarySearch #Arrays #CPlusPlus #CodingInterview #ProblemSolving #50ImportantQuestions

🚀 #LeetcodePotd : 696 Count Binary Substrings | ⚡ Runtime 10 ms (Beats 87.5%) At first glance this looks like a string problem. Plot twist: it’s actually a pattern compression + greedy counting problem. 🧠 Problem Insight We need substrings where: Equal number of 0s and 1s Each group must be consecutive ✔ 0011 → valid ❌ 0101 → invalid (not grouped) So the task is NOT checking all substrings (that would be O(n²) — instant rejection in interviews). Instead, observe the structure: Binary string = runs of identical characters Example: 00110011 → group lengths = [2,2,2,2] Now the magic rule: A valid substring exists whenever two adjacent groups exist. Count = min(prevGroupLength, currGroupLength) Because we can only pair consecutive blocks. 📊 Complexity Analysis MetricValueTime ComplexityO(n) — single passSpace ComplexityO(1) — only countersRuntime10 ms (Beats 87.5%)Memory46.35 MB (Beats 72.72%)💡 Why This Works We’re not counting substrings. We’re counting boundaries between groups. Every boundary generates substrings: 000111 ↑ boundary Possible: 01, 0011, 000111 → limited by smaller side So instead of brute force substring generation, we perform run-length compression on the fly. This is a classic: Transform problem → compress structure → greedy count Interviewers love this pattern because it shows pattern recognition > brute force coding. 🔥 Key Takeaway If your solution iterates over all substrings → you missed the abstraction. Strong candidates don’t solve the problem. They solve the structure of the problem. #leetcode #leetcode696 #datastructures #algorithms #dsa #codinginterview #interviewprep #softwareengineering #computerscience #programming #java #javaprogramming #strings #greedyalgorithm #patterns #problemSolving #coding #developer #engineering #tech #100daysofcode #competitiveprogramming #placementprep #techcareers #code #codinglife #geeksforgeeks #learning #optimization #timecomplexity #spacecomplexity #codingcommunity #students #futureengineer #devcommunity

Most people solve hundreds of LeetCode problems and still fail interviews Why? Because they're memorizing solutions, not learning patterns. I created a different approach: A curated set of 100 problems organized by topic, where each problem teaches you a reusable pattern. Think of it as your DSA curriculum, not just a problem list. 📚 𝗪𝗵𝗮𝘁'𝘀 𝗶𝗻𝘀𝗶𝗱𝗲: ✓ Arrays - The foundation (Two Sum, Kadane's, etc.) ✓ Strings - Pattern matching mastery ✓ Linked Lists - Pointer techniques ✓ Stacks & Queues - Order-based problems ✓ Trees & BST - Hierarchical thinking ✓ Recursion & Backtracking - Breaking down problems ✓ Dynamic Programming - The interview differentiator ✓ Graphs - Real-world modeling ✓ Heaps - Efficient priority handling 10 problems per topic. Each builds on the last. Each teaches something transferable. Stop grinding randomly. Start learning systematically. If you’ve felt stuck grinding problems, this shift matters. #SoftwareDevelopment #CodingInterviews #DSA #TechJobs #LeetCode

🚀 50 Important Coding Questions – Question 21/50 🔹 Reverse Linked List | LeetCode (Easy) A core Linked List problem that every coding interview candidate must master 👇 📌 Problem Statement Given the head of a singly linked list, reverse the list and return the new head. 💡 Optimized Approach (Iterative – Three Pointers) Use three pointers: 👉 prev → previous node 👉 curr → current node 👉 next → next node Steps: 1️⃣ Store next node 2️⃣ Reverse current pointer 3️⃣ Move pointers forward ⏱ Time Complexity: O(n) 📦 Space Complexity: O(1) ✅ Why this problem is important? ✔ Foundation for all Linked List problems ✔ Tests pointer manipulation skills ✔ Frequently asked in interviews ✔ Needed for problems like Reverse in K-groups, Palindrome Linked List 📌 LeetCode Result: ✔ Accepted ⚡ Runtime: 0 ms (Beats 100%) 📊 Memory Efficient 🔔 This is Question 21 of my “50 Important Coding Questions” series. Linked Lists unlocked 🔓 Keep going 💪 👉 Question 22 coming soon… #DSA #LeetCode #ReverseLinkedList #LinkedList #Pointers #CPlusPlus #CodingInterview #ProblemSolving #50ImportantQuestions