Data Structures and Algorithms?

An Array is fundamental data structure. A Hash Table is another. Now you can search,sort, copy etc values of those data structures by applying search or sort algorithms on them. The performance or complexity of these algorithms can be measured using Big O notation.

Since you are learning javascript here is an example of searching an an array without any built in functions. This algorithm is Big O(n) where n is the size of the array. The performance is linear to the size of the array

function find5(array) {
   for(var i = 0; i<array.length;i++) {
          if(array[i] === 5) {
               return true;
          }
   }
   return false;
}
let arr = [1,2,3,4,5,6,7,8,9,10];
find5(arr) //Big O(n)

If the array has 1000 or 10000 items in it. The performance of this algorithm directly depends on the size of the array. Which is why Big O is O(n).

Another example is Big O(1) which means the performance is constant. Regardless of the size of the input.

function getFirstItem(array) {
      return array[0];
}
let arr = [1,2,3,4,5,6,7,8,9,10];
getFirstItem(arr); //Big O(1)

The peformance is constant. Regardless if the array contained 1000 or 100 000 000 items.

This all ties back to Data Strucutures (the array in this example) and algorithms (the mechanism that is applied on the data structure).