Check if original Array is retained after performing XOR with M exactly K times
Last Updated :
29 May, 2022
Given an array A and two integers M and K, the task is to check and print "Yes", if the original array can be retained by performing exactly 'K' number of bitwise XOR operations of the array elements with 'M'. Else print "No".
Note: XOR operation can be performed, on any element of the array, for 0 or more times.
Examples:
Input: A[] = {1, 2, 3, 4}, M = 5, K = 6
Output: Yes
Explanation:
If the XOR is performed on 1st element, A[0], for 6 times, we get A[0] back. Therefore, the original array is retained.
Input: A[] = {5, 9, 3, 4, 5}, M = 5, K = 3
Output: No
Explanation:
The original array cant be retained after performing odd number of XOR operations.
Approach: This problem can be solved using the XOR property
A XOR B = C and C XOR B = A
It can be seen that:
- if even number of XOR operations are performed for any positive number, then the original number can be retained.
- However, 0 is an exception. If both odd or even number of XOR operations are performed for 0, then the original number can be retained.
- Therefore, if K is even and M is 0, then the answer will always be Yes.
- If K is odd and 0 is not present in the array, then the answer will always be No.
- If K is odd and the count of 0 is at least 1 in the array then, the answer will be Yes.
Below is the implementation of the above approach:
C++
// C++ implementation for the
// above mentioned problem
#include <bits/stdc++.h>
using namespace std;
// Function to check if original Array
// can be retained by performing XOR
// with M exactly K times
string check(int Arr[], int n,
int M, int K)
{
int flag = 0;
// Check if O is present or not
for (int i = 0; i < n; i++) {
if (Arr[i] == 0)
flag = 1;
}
// If K is odd and 0 is not present
// then the answer will always be No.
if (K % 2 != 0
&& flag == 0)
return "No";
// Else it will be Yes
else
return "Yes";
}
// Driver Code
int main()
{
int Arr[] = { 1, 1, 2, 4, 7, 8 };
int M = 5;
int K = 6;
int n = sizeof(Arr) / sizeof(Arr[0]);
cout << check(Arr, n, M, K);
return 0;
}
Java
import java.util.*;
class GFG{
// Function to check if original Array
// can be retained by performing XOR
// with M exactly K times
static String check(int []Arr, int n,
int M, int K)
{
int flag = 0;
// Check if O is present or not
for (int i = 0; i < n; i++) {
if (Arr[i] == 0)
flag = 1;
}
// If K is odd and 0 is not present
// then the answer will always be No.
if (K % 2 != 0
&& flag == 0)
return "No";
// Else it will be Yes
else
return "Yes";
}
// Driver Code
public static void main(String args[])
{
int []Arr = { 1, 1, 2, 4, 7, 8 };
int M = 5;
int K = 6;
int n = Arr.length;
System.out.println(check(Arr, n, M, K));
}
}
// This code is contributed by Surendra_Gangwar
Python3
# Python3 implementation for the
# above mentioned problem
# Function to check if original Array
# can be retained by performing XOR
# with M exactly K times
def check(Arr, n, M, K):
flag = 0
# Check if O is present or not
for i in range(n):
if (Arr[i] == 0):
flag = 1
# If K is odd and 0 is not present
# then the answer will always be No.
if (K % 2 != 0 and flag == 0):
return "No"
# Else it will be Yes
else:
return "Yes";
# Driver Code
if __name__=='__main__':
Arr = [ 1, 1, 2, 4, 7, 8 ]
M = 5;
K = 6;
n = len(Arr);
print(check(Arr, n, M, K))
# This article contributed by Princi Singh
C#
// C# implementation for the
// above mentioned problem
using System;
class GFG
{
// Function to check if original Array
// can be retained by performing XOR
// with M exactly K times
static String check(int []Arr, int n,int M, int K)
{
int flag = 0;
// Check if O is present or not
for (int i = 0; i < n; i++) {
if (Arr[i] == 0)
flag = 1;
}
// If K is odd and 0 is not present
// then the answer will always be No.
if (K % 2 != 0
&& flag == 0)
return "No";
// Else it will be Yes
else
return "Yes";
}
// Driver code
public static void Main(String[] args)
{
int []Arr = { 1, 1, 2, 4, 7, 8 };
int M = 5;
int K = 6;
int n = Arr.Length;
Console.Write(check(Arr, n, M, K));
}
}
// This code is contributed by shivanisinghss2110
JavaScript
<script>
// Javascript implementation for the
// above mentioned problem
// Function to check if original Array
// can be retained by performing XOR
// with M exactly K times
function check(Arr, n, M, K)
{
let flag = 0;
// Check if O is present or not
for (let i = 0; i < n; i++) {
if (Arr[i] == 0)
flag = 1;
}
// If K is odd and 0 is not present
// then the answer will always be No.
if (K % 2 != 0
&& flag == 0)
return "No";
// Else it will be Yes
else
return "Yes";
}
// Driver Code
let Arr = [ 1, 1, 2, 4, 7, 8 ];
let M = 5;
let K = 6;
let n = Arr.length;
document.write(check(Arr, n, M, K));
</script>
Time Complexity: O(N), as we are using a loop to traverse N times so it will cost us O(N) time
Auxiliary Space: O(1), as we are not using any extra space.
Similar Reads
DSA Tutorial - Learn Data Structures and Algorithms DSA (Data Structures and Algorithms) is the study of organizing data efficiently using data structures like arrays, stacks, and trees, paired with step-by-step procedures (or algorithms) to solve problems effectively. Data structures manage how data is stored and accessed, while algorithms focus on
7 min read
Quick Sort QuickSort is a sorting algorithm based on the Divide and Conquer that picks an element as a pivot and partitions the given array around the picked pivot by placing the pivot in its correct position in the sorted array. It works on the principle of divide and conquer, breaking down the problem into s
12 min read
Merge Sort - Data Structure and Algorithms Tutorials Merge sort is a popular sorting algorithm known for its efficiency and stability. It follows the divide-and-conquer approach. It works by recursively dividing the input array into two halves, recursively sorting the two halves and finally merging them back together to obtain the sorted array. Merge
14 min read
Data Structures Tutorial Data structures are the fundamental building blocks of computer programming. They define how data is organized, stored, and manipulated within a program. Understanding data structures is very important for developing efficient and effective algorithms. What is Data Structure?A data structure is a st
2 min read
Bubble Sort Algorithm Bubble Sort is the simplest sorting algorithm that works by repeatedly swapping the adjacent elements if they are in the wrong order. This algorithm is not suitable for large data sets as its average and worst-case time complexity are quite high.We sort the array using multiple passes. After the fir
8 min read
Breadth First Search or BFS for a Graph Given a undirected graph represented by an adjacency list adj, where each adj[i] represents the list of vertices connected to vertex i. Perform a Breadth First Search (BFS) traversal starting from vertex 0, visiting vertices from left to right according to the adjacency list, and return a list conta
15+ min read
Binary Search Algorithm - Iterative and Recursive Implementation Binary Search Algorithm is a searching algorithm used in a sorted array by repeatedly dividing the search interval in half. The idea of binary search is to use the information that the array is sorted and reduce the time complexity to O(log N). Binary Search AlgorithmConditions to apply Binary Searc
15 min read
Insertion Sort Algorithm Insertion sort is a simple sorting algorithm that works by iteratively inserting each element of an unsorted list into its correct position in a sorted portion of the list. It is like sorting playing cards in your hands. You split the cards into two groups: the sorted cards and the unsorted cards. T
9 min read
Array Data Structure Guide In this article, we introduce array, implementation in different popular languages, its basic operations and commonly seen problems / interview questions. An array stores items (in case of C/C++ and Java Primitive Arrays) or their references (in case of Python, JS, Java Non-Primitive) at contiguous
4 min read
Sorting Algorithms A Sorting Algorithm is used to rearrange a given array or list of elements in an order. For example, a given array [10, 20, 5, 2] becomes [2, 5, 10, 20] after sorting in increasing order and becomes [20, 10, 5, 2] after sorting in decreasing order. There exist different sorting algorithms for differ
3 min read