What is complexity analysis in algorithms?

What is complexity analysis in algorithms?

Complexity analysis is the study of how the resource requirements of an algorithm grow with the size of the input.

Why is it important to analyze the complexity of algorithms?

Analyzing complexity helps in understanding the efficiency of algorithms, guiding us to choose the best one for a given problem.

Can you explain time complexity and space complexity?

Time complexity measures the time an algorithm takes to complete, while space complexity measures the memory it uses.

What are some common notations used in complexity analysis?

Common notations include Big O, Big Theta, and Big Omega, which describe upper, tight, and lower bounds of complexity.

Can you give an example of an algorithm with its complexity analysis?

Sure! For example, the binary search algorithm has a time complexity of O(log n) because it divides the search space in half each time.