What is Big O analysis and can you give me some examples?

What is Big O analysis and can you give me some examples?

Big O analysis is a way to describe the performance or complexity of an algorithm. It focuses on how the runtime or space requirements grow as the input size increases. For example, O(n) means the time grows linearly with the input size.

Can you provide an example of an algorithm with O(n^2) complexity?

Sure! A common example of an O(n^2) algorithm is the bubble sort. In bubble sort, each element is compared with every other element, leading to a quadratic growth in the number of comparisons as the input size increases.

What about an example of O(log n) complexity?

An example of O(log n) complexity is binary search. In binary search, the algorithm divides the search interval in half repeatedly, which results in a logarithmic growth in the number of comparisons needed to find an element.

How does O(1) complexity work?

O(1) complexity, also known as constant time complexity, means that the algorithm's runtime does not change regardless of the input size. An example is accessing an element in an array by its index.