Officially, the time complexity of the algorithm for this article is said to be N operations, where N is the number of elements in the unordered array plus the dummy elements. In this case, N is 15. So the time complexity for this algorithm is 15. ...
Coming up with time and space complexity for your solutions (see Big-O below) Testing your solutions There is a great intro for methodical, communicative problem-solving in an interview. You'll get this from the programming interview books, too, but I found this outstanding:Algorithm design can...
But time complexity wise, it would takeO(n+k.logn)which is better thanO(n.logk), right? (assuming k to be any number smaller than n) Then why is theO(n.logk)version preferred? Why is it mentioned everywhere and used by the std template?
To prove the correctness of a greedy algorithm, we must prove that an optimal solution to the original problem always makes the greedy choice, so that the greedy choice is always safe. TF To sort N records by quick sort, the worst-case time complexity is Ω(NlogN). TF...
When we use a heap to pop or push values, we will perform the function of heapify at the same time to ensure the heap is in the form of a min-heap. Heapify is the process of creating a heap data structure from a binary tree. Similarly, before each element is pushed into the heap...