O(n^2).md

O(n^2) -- Quadratic

This notation is characterized by having a complexity proportional to the square of our input.

It has a high cost and is not recommended for large data, we can commonly find it in cycles such as for with nested iterations, where each element of our input must be compared with other item.

const arrayOf10 = new Array(10).fill(0).map((_, i) => i + 1)
const arrayOf100 = new Array(100).fill(0).map((_, i) => i + 1)
const arrayOf1000 = new Array(1000).fill(0).map((_, i) => i + 1)


const myOperation = (array) => { // O(n^2)
  array.forEach(element1 => { // O(n)
    array.forEach(element2 => { // O(n)
      console.log([element1, element2]) // O(1)
    });
  });
}

myOperation(arrayOf10) // O(n^2) => Quadratic Time Complexity == O(10^2) => Will require 100 operations to complete the task
myOperation(arrayOf100) // O(n^2) => Quadratic Time Complexity == O(100^2) => Will require 10000 operations to complete the task
myOperation(arrayOf1000) // O(n^2) => Quadratic Time Complexity == O(1000^2) => Will require 1000000 operations to complete the task... don't try it at home.