Big O Performance of Arrays and Objects in JavaScript

Big O Performance of Arrays and Objects in JavaScript

In this tutorial, we will discuss about Big O Performance of Arrays and Objects in JavaScript. We take the help of Big-O notation to compare and contrast the runtime for arrays and objects to understand them clearly.

The efficiency of the program would be directly relying on Time Complexity when we deal with a huge amount of data to perform operations like searching, sorting, access, insertion and removal of an element.

We could selectively use objects and arrays based on the need to enhance the performance. We take the help of Big-O notation to compare and contrast the runtime for arrays and objects to understand them clearly.

Let us understand the concept of Big-O notation quickly in terms of time complexity.

Big-0 notation helps in calculating the efficiency of an algorithm formally.

To compare algorithms, we should not consider:

  • Execution times — as they are specific to a particular computer.
  • Number of statements executed — as it varies with programming language.

The ideal way of comparing algorithms is by calculating the number of operations the computer has to perform based on the size of an input.

Let us see it by a simple example. Calculate the sum of all numbers from 1 up to (and including) some number n.

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