Asymptotic running time of for-loops
I have this question which I need answered:
What does ‘upper bound’ mean in context of BigO?
My computer science teacher says Big O has an upper bound but no lower bound. When I look at a graph of an algorithm mapped out using BigO though, there isn’t an upper bound at all. The upper limit goes on forever. So what do it mean to say there is an upper bound in the context of BigO?
Big O notation for the algorithm
What would be the big o for the algo:
Algorithms: How do I sum O(n) and O(nlog(n)) together?
I have the follow algorithm which finds duplicates and removes them:
Algorithms: How do I sum O(n) and O(nlog(n)) together?
I have the follow algorithm which finds duplicates and removes them:
Algorithms: How do I sum O(n) and O(nlog(n)) together?
I have the follow algorithm which finds duplicates and removes them:
Loop runtime question
I had an exam today and I feel that I did pretty well, except I could not for the life of me figure out what appears to be an unbelievably simple question.
Quickest sorting algorithm for sorting a low number of integers
I am making a program on my spare time that I want to run as quickly as possible. The program is written in C.
Big O notation allocate array of N element
In Big O notation, allocate an array of N element is defined by O(1) or O(n) ?
For example in C#, if I allocate an array like this :
Big O notation allocate array of N element
In Big O notation, allocate an array of N element is defined by O(1) or O(n) ?
For example in C#, if I allocate an array like this :