I\'ve tried to come up with the Big O Running time of the following data structures. Are they Correct?
Lets say I have a routine that scans an entire list of n items 3 times, does a sort based on the size, and then bsearches that sorted list n times.The scans are O(n) time, the sort I will call O(n log
Article at http://leepoint.net/notes-java/algorithms/big-oh/bigoh.html says that Big O notation For accessing middle element in linked list is O(N) .should not it be O(N/2) .Assume we have 100 element
This may be more of a theoretical question but I\'m looking for a pragmatic answer. I plan to use Redis\'s Sorted Sets to store the ranking of a model in my database based on a calculated value. Curr
I\'m prepping for interviews, and some obvious interview questions such as counting frequency of characters in a string involve putting all of the characters into a Hashtable/Dictionary in order to ge
After reading this question and through the various Phone Book sorting scenarios put forth in the answer, I found the concept of the BOGO sort to be quite interesting.Certainly there is no use for thi
Radix sort\'s time complexity is O(kn) where n is the number of keys to be sorted and k is the key length. Similarly, the time complexity for the insert, delete, and lookup operations in a trie is O(k
The开发者_Python百科 approach I\'m referring to is the dual-pointer technique.Where the first pointer is a straightforward iterator and the second pointer goes through only all previous values relativ
I have never heard this before, or maybe I have heard it in other terms? The context is that for adjacency lists, the time to list all vertices adjacent to u is Θ(deg(u)).
I was just reading another question and this code intrigued me: for(i = 0; i < n; i++) { for(j = 0; j < i*i; j++)
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