O(N) describes an algorithm whose performance will grow linearly and in direct proportion to the size of the input data set.

The example below also demonstrates how Big O supports the worst-case performance scenario.

const nums = [1, 2, 3, 4, 5];
let sum = 0;
for (let num of nums) {
  sum += num;
}

Again, the question is: how many input operations are required? Here, you need to iterate over each element, i.e., an operation for each element. The larger the array, the more operations.

Using Big O notation: O(n), or "complexity of order n." Such algorithms are also called "linear" or that the algorithm "scales linearly."

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