L-05 | Time complexity | How to find out time complexity of iterative algorithms?

Computing the time complexity of algorithms is essential to select the most efficient algorithms among various algorithms. There can be two types of algorithms: one is iterative, and the other one is recursive. In iterative algorithms, loops are used to carry out the task, such as 'for' loop, 'while' loop, and 'do while' loop. In this video lecture, the method of computing the time complexity of iterative algorithms is discussed in detail with various examples. There are 17 examples of different types, including nested and consecutive loop concepts. The time complexity of the algorithms is provided in the asymptotic upper bound called 'Big Oh'.

To understand the basic idea of time complexity and asymptotic notations such as 'Big Oh', 'Big Omega', and 'Theta', please refer to the following video lectures from my 'Design and analysis of algorithms' playlist. The links to the lectures are given below. Thank you.