Computational Complexity:

Computational complexity is a branch of computer science that deals with the study of the resources (time, memory, etc.) required to solve computational problems. It provides a framework for measuring and comparing the efficiency of algorithms, enabling us to classify problems into different complexity classes.

When discussing computational complexity, the Big O notation plays a crucial role. It allows us to express the upper bound of an algorithm's growth rate as a function of the input size. By characterizing the relationship between input size and resource usage, the Big O notation gives us a bird's-eye view of an algorithm's efficiency.

This graph is a big -O complexity graph which is used to describe the time complexity of algorithms. It calculates the time taken to run an algorithm as the input grows and in different words we can say it calculates the worst- case time complexity of an algorithm.