Rotate Array LeetCode Solution

🚀 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

🚀 50 Important Coding Questions – Question 27/50 🔹 Sort List | LeetCode (Medium) A very important Linked List problem that teaches sorting using Merge Sort 📚 📌 Problem Statement Given the head of a linked list, sort it in ascending order. 💡 Optimal Approach – Merge Sort on Linked List Why Merge Sort? Because Linked Lists don’t support random access like arrays. 👉 Steps 1️⃣ Find middle of list using slow & fast pointers 2️⃣ Split list into two halves 3️⃣ Recursively sort both halves 4️⃣ Merge sorted lists 🧠 Why this problem is important? ✔ Teaches Merge Sort logic ✔ Important interview question ✔ Helps in advanced Linked List problems ✔ Improves recursion understanding ⏱ Time Complexity: O(n log n) 📦 Space Complexity: O(log n) (recursion stack) 👉 My approach used array conversion + sorting, but Merge Sort is the optimal in interviews. 📌 LeetCode Result: ✔ Accepted ⚡ Efficient solution 🔔 This is Question 27 of my “50 Important Coding Questions” series. Linked List concepts getting stronger 💪 👉 Question 28 coming soon… #DSA #LeetCode #LinkedList #MergeSort #CodingInterview #CPlusPlus #ProblemSolving #50ImportantQuestions

🚀 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 15/50 🔹 Reverse Vowels of a String | LeetCode (Easy) A simple but effective Two Pointers string problem that improves string traversal logic 👇 📌 Problem Statement Given a string s, reverse only all the vowels in the string and return it. 👉 Vowels = a, e, i, o, u (case-insensitive) 💡 Optimized Approach (Two Pointers) 1️⃣ Use two pointers → start & end 2️⃣ Move pointers until vowels are found 3️⃣ Swap vowels 4️⃣ Continue until pointers meet ⏱ Time Complexity: O(n) 📦 Space Complexity: O(1) ✅ Why this problem is important? ✔ Strengthens Two Pointer technique ✔ Improves string manipulation skills ✔ Common warm-up interview question ✔ Builds intuition for palindrome & substring problems 📌 LeetCode Result: ✔ Accepted ⚡ Runtime: 0 ms (Beats 100%) 📊 Memory Efficient 🔔 This is Question 15 of my “50 Important Coding Questions” series. Small steps every day = Big results 💪 👉 Question 16 coming soon… #DSA #LeetCode #ReverseVowels #TwoPointers #Strings #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

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 5/50 🔹 Range Sum Query – Immutable | LeetCode (Easy) A core prefix sum problem that introduces preprocessing for fast queries — extremely useful in real-world systems 👇 📌 Problem Statement Given an integer array nums, handle multiple queries of the form 👉 sumRange(left, right) efficiently. 💡 Optimized Approach (Prefix Sum Array) Precompute prefix sums Answer each range query in O(1) time Formula used: sum(l, r) = prefix[r] − prefix[l − 1] ⏱ Time Complexity: Preprocessing: O(n) Each Query: O(1) 📦 Space Complexity: O(n) ✅ Why this problem is important? ✔ Introduces Prefix Sum technique ✔ Teaches trade-off between preprocessing & query time ✔ Foundation for many range query & DP problems ✔ Common in interview & competitive programming 📌 LeetCode Result: ✔ Accepted ⚡ Runtime: 0 ms (Beats 100%) 📊 Memory Efficient 🔔 This is Question 5 of my “50 Important Coding Questions” series. Follow for daily DSA concepts, optimized code, and interview-focused problems 💻✨ 👉 Question 6 coming soon… #DSA #LeetCode #PrefixSum #RangeSumQuery #Arrays #CPlusPlus #CodingInterview #50ImportantQuestions

🚀 50 Important Coding Questions – Question 7/50 🔹 Container With Most Water | LeetCode (Medium) A classic Two Pointers problem that tests your ability to optimize brute force logic into an elegant solution 👇 📌 Problem Statement Given n vertical lines where the iᵗʰ line has height height[i], find two lines that together with the x-axis form a container that holds the maximum amount of water. 💡 Optimized Approach (Two Pointers) Start with pointers at both ends Calculate area = width × min(height[left], height[right]) Move the pointer with the smaller height inward ⏱ Time Complexity: O(n) 📦 Space Complexity: O(1) ✅ Why this problem is important? ✔ Perfect example of Two Pointers optimization ✔ Shows how greedy movement leads to optimal results ✔ Very popular in FAANG & product-based interviews ✔ Builds intuition for width–height trade-off problems 📌 LeetCode Result: ✔ Solved using optimal two-pointer strategy ⚡ Efficient & interview-ready 🔔 This is Question 7 of my “50 Important Coding Questions” series. Follow for daily DSA problems, clean logic, and interview insights 💻✨ 👉 Question 8 coming soon… #DSA #LeetCode #TwoPointers #ContainerWithMostWater #CPlusPlus #CodingInterview #ProblemSolving #50ImportantQuestions

🚀 50 Important Coding Questions – Question 20/50 🔹 Longest Consecutive Sequence | LeetCode (Medium) A powerful Hash Set problem that teaches how to detect sequences efficiently without sorting 👇 📌 Problem Statement Given an unsorted array of integers nums, return the length of the longest consecutive elements sequence. 👉 Must solve in O(n) time. 💡 Optimized Approach (Hash Set) 1️⃣ Store all numbers in a set 2️⃣ Only start counting when num-1 is NOT in set 3️⃣ Keep checking num+1 until sequence ends 4️⃣ Track maximum length ⏱ Time Complexity: O(n) 📦 Space Complexity: O(n) ✅ Why this problem is important? ✔ Strengthens Hash Set concepts ✔ Teaches sequence detection logic ✔ Very common in FAANG interviews ✔ Shows how to reduce sorting to linear time 📌 LeetCode Result: ✔ Accepted ⚡ Efficient O(n) solution 🔔 This is Question 20 of my “50 Important Coding Questions” series. Almost halfway — keep the grind going 💪 👉 Question 21 coming soon… #DSA #LeetCode #LongestConsecutiveSequence #HashSet #Arrays #CPlusPlus #CodingInterview #ProblemSolving #50ImportantQuestions

🚀 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