Longest Subarray with Sum K | Prefix Sum + HashMap Explained | Java DSA Interview | Coding Help скачать в хорошем качестве

Longest Subarray with Sum K | Prefix Sum + HashMap Explained | Java DSA Interview | Coding Help

00:00 What You Will Learn in This Video 01:35 Problem Introduction 02:25 Brute Force Approach 03:29 Why Sliding Window Fails 04:15 Visual Example 08:45 Key Observation & Prefix Sum Concept + HashMap Dry Run 12:48 Java Code Implementation 14:00 Related Problems You Can Solve 14:17 Final Summary & Tips In this video on Coding Help, we solve the popular DSA interview problem “Longest Subarray with Sum = K” using the Prefix Sum + HashMap technique in Java. Most people try Sliding Window or Brute Force and get wrong answers, especially when negative numbers are present. In this tutorial, you will learn the correct O(n) approach, the logic behind it, and how this one pattern helps you solve many other interview problems. 🔍 What You Will Learn Why Sliding Window fails in this problem Prefix Sum concept explained simply HashMap trick interviewers expect Dry Run + Intuition Optimized Java Code Common Mistakes to Avoid Time & Space Complexity 🧠 After Understanding This Problem, You Can Also Solve: Longest Subarray with Sum = 0 Subarray with Equal 0s and 1s Longest Subarray with Equal Even and Odd Subarray Sum Divisible by K Count Subarrays with Sum = K This is not just one problem — it’s a DSA pattern that appears in multiple coding interviews. 🚀 Complexity Time Complexity: O(n) Space Complexity: O(n) #DSA #Java #PrefixSum #HashMap #CodingInterview #LeetCode #ArrayProblems #JavaDSA #InterviewPreparation #CodingHelp