# program to tell if a number is a perfect square with code examples

As mathematics is one of the important subjects we all study right from our school days, we come across various concepts that continue to baffle us even today. One such concept is the perfect square numbers. We often find ourselves wondering if a number is a perfect square or not. A perfect square number is defined as an integer that can be obtained by squaring another integer. For instance, 1, 4, 9, 16, 25, and 36, etc. are perfect squares.

But what if we want to identify if a number is a perfect square or not programmatically? Good news! Different programming languages offer a great set of functions or algorithms that can help us identify whether a number is a perfect square or not.

The most prominent algorithm is the integer square root algorithm, which utilizes the property of perfect squares i.e., all perfect squares are integers to identify if a number is a perfect square or not. But before we dive into the code examples, let’s understand what an integer square root algorithm is.

The integer square root algorithm, also known as the Babylonian method, is a simple algorithmic approach to calculate the square root of a given integer. This algorithm starts by guessing the square root of the given integer, and then repeatedly refines the estimate by averaging it out with the original number divided by the current estimate. This process continues until the estimate is within an acceptable range of accuracy.

Now that we have grasped the concept behind the integer square root algorithm, let's move on to the code examples.

Python:

Python provides a straightforward approach to check for perfect squares by utilizing the math module. Here is the code snippet:

```import math
def isPerfectSquare(number:int)->bool:
root = int(math.sqrt(number))
if root * root == number:
return True
else:
return False
```

In this code snippet, we imported the required math module, then defined a function called isPerfectSquare that takes an integer as input and returns True if the input is a perfect square else returns False. Inside the isPerfectSquare function, we converted the input number to an integer square root, and if the square of the obtained root is the same as the input number, we returned True, else False.

Java:

Java also provides us with a simple approach to check for perfect squares. Here is the code snippet:

```public static boolean isPerfectSquare(int num) {
int root = (int) Math.sqrt(num);
if (root * root == num)
return true;
else
return false;
}
```

In this code block, we created a function called isPerfectSquare that takes an integer as input and returns True if the input is a perfect square, else returns False. We calculated the integer square root using the Math.sqrt method and cast it back to an integer. If the square of this root is equal to the input number, we return True, else False.

C++:

In C++, we used the same approach as Java. Here is the code snippet:

```#include <bits/stdc++.h>
using namespace std;

bool isPerfectSquare(int num) {
int root = (int) sqrt(num);
if (root * root == num)
return true;
else
return false;
}

int main() {
int num = 25;
if (isPerfectSquare(num))
cout<<num<<" is a perfect square"<<endl;
else
cout<<num<<" is not a perfect square"<<endl;
return 0;
}
```

In this sample code, we have created a function called isPerfectSquare that takes an integer as input and returns True if the input is a perfect square, else False. We calculated the integer square root using the sqrt method from the mathematics library and cast it back to an integer. If the square of this root is equal to the input number, we return True, else False. In the main function, we passed the input number as 25 and checked whether it is a perfect square or not.

Conclusion:

In conclusion, identifying if a number is a perfect square is a commonly asked question from school mathematics. By using any of the above programming languages, you can quickly determine whether a number is a perfect square or not programmatically. The integer square root algorithm is an effective approach to perform the calculation accurately no matter the programming language or the size of the input. It is an essential concept to master when working with mathematical algorithms.

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## Popular questions

Sure, here are five commonly asked questions on writing a program to tell if a number is a perfect square with code examples along with their answers:

1. What exactly is a perfect square number?
Answer: A perfect square number is defined as an integer that can be obtained by squaring another integer. For instance, 1, 4, 9, 16, 25, and 36, etc. are perfect squares.

2. How can you check if a number is a perfect square?
Answer: You can check if a number is a perfect square by using the integer square root algorithm, which checks whether the square of the integer square root of the number is the same as the number itself.

3. Which programming languages offer built-in functions for checking perfect squares?
Answer: Many programming languages offer built-in functions for checking perfect squares. Python has the math module, Java has the Math.sqrt method, and C++ has the sqrt function from the mathematics library.

4. Can we check for perfect squares without using built-in functions or algorithms?
Answer: Yes, we can check for perfect squares without using built-in functions or algorithms by iterating over all the integers until the square of the integer is greater than or equal to the input number.

5. Why should we use the integer square root algorithm to check for perfect squares?
Answer: We should use the integer square root algorithm to check for perfect squares because it is a very efficient approach that can accurately identify a perfect square no matter the input size. Additionally, using built-in functions or algorithms can save a lot of time and effort.

### Tag

SquareCheck ##### Ajay Kemparaj
Throughout my career, I have held positions ranging from Associate Software Engineer to Principal Engineer and have excelled in high-pressure environments. My passion and enthusiasm for my work drive me to get things done efficiently and effectively. I have a balanced mindset towards software development and testing, with a focus on design and underlying technologies. My experience in software development spans all aspects, including requirements gathering, design, coding, testing, and infrastructure. I specialize in developing distributed systems, web services, high-volume web applications, and ensuring scalability and availability using Amazon Web Services (EC2, ELBs, autoscaling, SimpleDB, SNS, SQS). Currently, I am focused on honing my skills in algorithms, data structures, and fast prototyping to develop and implement proof of concepts. Additionally, I possess good knowledge of analytics and have experience in implementing SiteCatalyst. As an open-source contributor, I am dedicated to contributing to the community and staying up-to-date with the latest technologies and industry trends.
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