Anyone can write code, but writing the most optimal one is what counts. Big O notation is used in Computer Science to describe the performance or complexity of an algorithm, in other words it can be used to describe the execution time required or the space used (e.g. in memory or on disk) by an algorithm. Here we have two main aspects: Time and Space complexity, our goal is to be as close to O(1) and as far from O(n!) as possible.
Alternative Big O notations(fun) version:
O(1) = O(yeah)
O(log n) = O(nice)
O(nlogn) = O(k-ish)
O(n) = O(ok)
O(n²) = O(my)
O(2ⁿ) = O(no)
O(n^n) = O(fuck)
O(n!) = O(mg!)
Was that helpful? Let me know :)