Linked Questions

Big-O describes an upper bound on run time. Is that not the definition of "worst-case"? For example, how can we say that a hash table insertion require O(1) time on average? Constant time is the best ...

Regarding time complexity I've read conflicting things: 1) That it is worst case. 2) That is average case. For example if I want to know the time complexity for inserting into an arbitrary point in ...

If an algorithm has running time of $\Theta(n^2)$, is it possible to have a best-case running time of $\Omega(n)$? Or is the fastest running time only $c n^2$ for some constant factor $c$?

In the big O section of Cracking the Coding Interview 6th edition, I read the following. ...

If it is given that a program has a worst case running time of $O(n)$, then is it still okay to define the running time as being $O(n^2)$. By definition, this seems corrects since Big-Oh is ...

I don't understand why O notation is the worst case. If this notations describes a function f such that 0 <= f(n) <= cg(n), we can see that in any case f will be smaller that the original ...

I wanted to understand how to establish both the lower $\Omega$ and upper bound $O$ on an algorithm to conclude it runs in $\Theta$ (note that I am not trying to prove that the algorithm is the most ...

From Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein Theorem 3.1 For any two functions $f(n)$ and $g(n)$, we have $f(n) = \Theta(g(n))$ if ...

I was reading the Cormen, Leiserson, Rivest and Stein textbook, Introduction to Algorithms. The book explained the three asymptotic notations literally very well. However, there was this paragraph: ...

I'm reading the CLRS book and there is a statement for instance, the running time of insertion sort is not $\Omega(n^2)$, since there exists an input for which insertion sort runs in $\Theta(n)$ ...

There are lots of questions about how to analyze the running time of algorithms (see, e.g., runtime-analysis and algorithm-analysis). Many are similar, for instance those asking for a cost analysis ...

In most introductory algorithm classes, notations like $O$ (Big O) and $\Theta$ are introduced, and a student would typically learn to use one of these to find the time complexity. However, there are ...

I mathematically understand $f(n) \in O(g(n))$ : $f(n)$ does not grow faster than $g(n)$. More formally, $\exists c, n_0$ s.t. $f(n) \leq cg(n) \forall n \geq n_0$. Similarly, $f(n) \in \Theta(g(n))$...

I would like to know why the following statement The running time of algorithm $A$ is at least $O(n^2)$ which means the best-case running time of $A$ is $O(n^2)$ is meaningless (CLRS page 53). ...

When discussing the worst case runtime $T(n)$ of an algorithm, we attempt to bound $T(n)$ above by some simple function $g(n)$, so that $T(n) = O(g(n))$. When discussing the best case runtime $T(n)$ ...