No talking here, only testing. int Sum1ToN(int n) { int ans = n*(n+1)/2; return ans; } int getSum(int n, int m) { int ans = 0; for(int i = 1; i <= n; ++i) for(int j = 1; j <= m; ++j) ans++; return ans; } int doRandomStuff(int n, int

To calculate Time Complexity, we must try to understand the code line-by-line and see how many operations it will have to do for a given set of inputs. After finding the approximate number of operations as a function of the input variable: 1. Get rid of those terms that will

In this article, I'll try to give you folks a brief idea about how much time codes with different time complexities take to run when given different sizes of inputs. Before diving in, I'd like to share that a C++ code can run around 2∗108

Now that we know, on a high level, what time & space complexities are, it's a good time to look at different ways to represent them and try to make sense of them practically. Let's clear out the make sense of it part right now. It&

Alright; after having understood time complexity, this should be fairly easy. We just learned that measuring time efficiency in terms of the absolute time it takes to run a code is not ideal. Similarly, we can't just say that the space complexity of a program is 73 bytes

Why did the algorithm go to therapy? It had an issue with time, and needed a safe space to sort it out! If I ask you, how time-efficient is this code you've written? What do you think will be the right way to measure it? What if you