Big O Bubble Sort

Physical Education Teacher
girl, kid, tennis @ Pixabay

If you’re familiar with the basics of sorting algorithms, you know that there are a lot of different ways to go about it. But what’s the best way? In this article, we’ll take a look at one particular algorithm – bubble sort – and see how it stacks up against the others.

What is Bubble Sort?

Bubble sort is a simple sorting algorithm that repeatedly steps through an array, compares adjacent pairs of elements and swaps them if they are in the wrong order. The pass through the array is repeated until the array is sorted.

This algorithm gets its name from the way smaller elements “bubble” to the top of the array.

The Different Types of Bubble Sort

There are many different types of bubble sort, each with its own advantages and disadvantages. Here are four of the most popular bubble sort methods:

1. Standard bubble sort. This is the most basic form of bubble sort. It repeatedly compares adjacent pairs of elements and swaps them if they are in the wrong order. This method is simple to implement but is very slow, since it has to compare every element in the array on each pass.

2. Optimized bubble sort. This version of bubble sort tries to reduce the number of comparisons by making sure that on each pass, the largest element isbubbled up to the end of the array. This can save a significant amount of time, but it still isn’t very fast compared to other sorting algorithms.

3. Cocktail sort. This is a variation of optimized bubble sort that sorts in both directions on each pass. It starts at the beginning of the array and bubbles up the smallest elements. Then it goes back to the end of the array andbubbles down the largest elements. This method saves time by not having to make as many passes over the array, but it is still slower than most other sorting algorithms.

4. Comb sort.

Pros and Cons of Bubble Sort

There are many sorting algorithms out there, each with its own set of pros and cons. Bubble sort is one of the more simple sorting algorithms, but that doesn’t mean it isn’t without its faults. Let’s take a look at the pros and cons of bubble sort so you can decide if it’s the right algorithm for your needs.


  • Easy to understand and implement
  • can be used on a variety of data types
  • Not very memory intensive


  • Not very efficient for large data sets
  • Can be slow for large data sets

What is the Big O Notation?

The Big O notation is a mathematical notation that describes the limiting behavior of a function when the argument tends to infinity. In computer science, it is used to characterize algorithms by how they scale with respect to the size of the input.

How to Calculate Big O Notation

When it comes to understanding Big O notation and how to calculate it, there are a few key things to keep in mind. First, Big O notation is used to measure the worst-case scenario for an algorithm. This means that if you were to run an algorithm multiple times, the longest amount of time it took to complete would be captured by the Big O notation.

Another thing to keep in mind is that Big O notation is concerned with the relative efficiency of an algorithm, not the absolute efficiency. In other words, if one algorithm has a Big O notation of O(n) and another has a Big O notation of O(n^2), the first algorithm is more efficient. However, if both algorithms take the same amount of time to complete, then the one with the lower Big O notation is more efficient.

Finally, it’s important to note that there are different types of efficiency that can be measured using Big O notation. The most common type is time complexity, which measures how long an algorithm takes to run. There’s also space complexity, which measures how much memory an algorithm uses.

Now that we’ve gone over the basics of Big O notation, let’s talk about how to actually calculate


The Big O notation is a tool that computer scientists use to measure the efficiency of algorithms. In this article, we looked at how to use the Big O notation to analyze the bubble sort algorithm. We saw that the worst case scenario for bubble sort is an array of n items, where n is the number of items in the array. This means that the time complexity of bubble sort is O(n).