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Largest Subarray of 0's and 1's
📝 Problem Description:
In this video, we'll be solving a classic problem: Finding the longest subarray of 0's and 1's in a given binary array. The challenge is to find a subarray with an equal number of 0's and 1's. This is an interesting problem that allows us to explore different approaches like hashmaps and cumulative sums to efficiently solve it.
Here's how the problem looks:
Given an array arr[] consisting of 0's and 1's, we need to determine the length of the longest contiguous subarray where the number of 0's equals the number of 1's.

💡 Example 1:

Input: [1, 0, 1, 1, 1, 0, 0]
Output: 6
Explanation: The longest subarray that has equal numbers of 0's and 1's is from index 1 to index 6, which contains 3 zeros and 3 ones.
💡 Example 2:

Input: [0, 0, 1, 1, 0]
Output: 4
Explanation: The subarray [0, 0, 1, 1] or [0, 1, 1, 0] has 2 zeros and 2 ones. Both subarrays have length 4, and hence, the result is 4.
💡 Example 3:

Input: [0]
Output: 0
Explanation: There are no subarrays where the number of 0's and 1's is equal. Therefore, the output is 0.
❗ Constraints:

The size of the array can be as large as 10^5.
Each element in the array will either be 0 or 1.
🎯 What you'll learn:

How to solve problems using hashmaps (or dictionaries) for efficient lookups.
Techniques like prefix sum or balance method.
Optimizing time complexity to O(N).
Handling edge cases and large input sizes.
🔑 Keywords/Hashtags:
#Arrays #Subarrays #ZeroOne #LongestSubarray #BinaryArray #ProblemSolving #InterviewQuestions #CodingChallenge #TechInterviews #Algorithm #HashMap #PrefixSum

⏰ Time Complexity: O(N)
Space Complexity: O(N)

Bitwise XOR of All Pairings
📝 Problem Description:
In this video, we'll tackle another exciting problem: Finding the bitwise XOR of all pairings between two arrays. You are given two 0-indexed arrays, nums1 and nums2, and you need to compute the XOR of all pairings of elements between the two arrays. After generating the resultant XOR array, the task is to return the XOR of all integers in that array.

💡 Example 1:

Input: nums1 = [2, 1, 3], nums2 = [10, 2, 5, 0]
Output: 13
Explanation: A possible nums3 array containing the XOR of all pairs is [8, 0, 7, 2, 11, 3, 4, 1, 9, 1, 6, 3].
The XOR of all elements in nums3 gives the result 13.
💡 Example 2:

Input: nums1 = [1, 2], nums2 = [3, 4]
Output: 0
Explanation: All possible XOR pairs are:
nums1[0] ^ nums2[0] → 1 ^ 3 = 2
nums1[0] ^ nums2[1] → 1 ^ 4 = 5
nums1[1] ^ nums2[0] → 2 ^ 3 = 1
nums1[1] ^ nums2[1] → 2 ^ 4 = 6
The XOR of all these results is 2 ^ 5 ^ 1 ^ 6 = 0, so the output is 0.
💡 How to Approach:

We generate all pairings between elements of nums1 and nums2, compute the XOR for each pair, and store it in a new array.
Finally, we compute the XOR of all the values in this array and return the result.
But, there's a more efficient way to calculate this directly using the properties of XOR.
❗ Constraints:

The length of the arrays nums1 and nums2 can be up to 10^5.
The values in the arrays are between 0 and 10^9.
🎯 What you'll learn:

Understanding the bitwise XOR operation and its properties.
How to compute the XOR of multiple elements efficiently.
The importance of recognizing patterns in bitwise operations to reduce time complexity.
Solving problems involving large data sets and optimizing your approach for better performance.
🔑 Keywords/Hashtags:
#BitwiseXOR #XOR #Arrays #Pairing #ProblemSolving #TechInterviews #CodingChallenge #Math #Algorithm #EfficientAlgorithms

⏰ Time Complexity: O(N * M), where N is the length of nums1 and M is the length of nums2.
Space Complexity: O(N * M)

⏳ Timestamps:
00:00 - Problem 1: Largest Subarray of 0's and 1's
05:58 - Problem 2: Bitwise XOR of All Pairings

Видео 16 January, 2025: GFG POTD🎯 | LEETCODE DAILY CHALLENGE💻 #gfg #gfgpotd #leetcode канала Terraacottaa