Uploaded December 2012 | Updated September 2026, 2 weeks ago
See complete series on time complexity here
youtube.com/playlist?list=PL2_aWCzGMAwI9HK8YPVBjElbLbI3ufctn
In this lesson, we will see how to deduce an expression for running time of a program/algorithm as a function of input size. We define a hypothetical model machine where our algorithm may execute and try to calculate the growth function for running time. Then we classify these functions into broad sets using big-oh or other asymptotic notations.
Pre-requisite: Basic knowledge of programming concepts.
See complete series on time complexity here
youtube.com/playlist?list=PL2_aWCzGMAwI9HK8YPVBjElbLbI3ufctn
In this lesson, we will see how to deduce an expression for running time of a program/algorithm as a function of input size. We define a hypothetical model machine where our algorithm may execute and try to calculate the growth function for running time. Then we classify these functions into broad sets using big-oh or other asymptotic notations.
Pre-requisite: Basic knowledge of programming concepts.










