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Скачать или смотреть Find the Repeating Element in Array | 7 Powerful Approaches Explained | DSA Interview Must-Know

  • NullPointer
  • 2025-12-21
  • 5
Find the Repeating Element in Array | 7 Powerful Approaches Explained | DSA Interview Must-Know
codingprogramminginterviewtech interviewsdesde interviewcoding practicetech job interviewsoftware engineeringSDE sheetSDE preparationgfgleetcodegeeksforgeekscompetitive programmingcoding questionfaangmaangcpppythonjavaC++dsa pattern questionsslow and fast pointersfind only repetitive element from 1 to n-1
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Описание к видео Find the Repeating Element in Array | 7 Powerful Approaches Explained | DSA Interview Must-Know

“7 Ways to Find the Duplicate Number | Brute → XOR → Floyd’s Cycle | Full DSA Guide”
“Find Duplicate in Array (1 to n-1) | ALL Approaches Explained | Interview Ready”
“Duplicate Number Problem | 7 Methods from Naive to Floyd’s Cycle Detection”

In this video, we solve a classic and very important DSA interview problem:

🔹 Given an array of size n containing numbers from 1 to n−1,
🔹 Exactly ONE number is repeated,
🔹 Your task is to find the repeating element.

What makes this video special is that we solve the same problem using **7 DIFFERENT APPROACHES**, starting from brute force and gradually moving to the most optimal and elegant solutions used in real interviews.

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🔥 APPROACHES COVERED IN THIS VIDEO

1️⃣ Naive Approach – Nested Loops
Time: O(n²), Space: O(1)

2️⃣ Sorting Based Approach
Time: O(n log n), Space: O(1)

3️⃣ Hash Set Approach
Time: O(n), Space: O(n)

4️⃣ Sum Formula (Mathematical Approach)
Time: O(n), Space: O(1)

5️⃣ XOR Based Approach
Time: O(n), Space: O(1)

6️⃣ Using Elements as Indexes (Sign Marking Technique)
Time: O(n), Space: O(1)

7️⃣ Floyd’s Cycle Detection Algorithm (Tortoise & Hare)
Time: O(n), Space: O(1) ⭐ (MOST IMPORTANT FOR INTERVIEWS)

Whether you're preparing for FAANG, product-based companies, coding rounds, or want to strengthen your fundamentals, this channel brings you the best structured DSA explanations with zero confusion.

Step-by-step logic
Mathematical reasoning
Multiple approaches (Naive → Optimized)
Time & Space complexity
Real interview insights
Clean and easy-to-understand code

Data Structures (Arrays, Strings, Stacks, Queues, Trees, Graphs, LinkedList, Hashing, Heaps)
Algorithms (Sorting, Searching, Binary Search, Greedy, DP, Recursion, Backtracking, Graph Algorithms)
Math Logic for coding (Number Theory, Combinatorics, Modular Arithmetic)
Coding interview questions with full proof and code
Competitive programming tricks and optimizations
LeetCode, GFG, Codeforces, HackerRank problem explanations
Pattern printing & logic building
Time complexity mastery

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Your support motivates me to create more high-quality content.

Tags:
#DSA #Coding #CompetitiveProgramming #Programmer #DataStructures #Algorithms
#LeetCode #GeeksForGeeks #CodingInterview #SoftwareEngineer #CodeWithMe
#MathInCode #Optimization #CP #Java #Python #C++ #LogicBuilding #ProblemSolving
#TechInterview #ProgrammingTutorial #ComputerScience #CodingChallenge
#DSATutorial #CodingForBeginners #Code #BinarySearch #Recursion #DynamicProgramming

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