I\'ve been having some problems trying to grasp the concept of big O notation. So, by definition big O is as follows, T(n) ∈ O(G(n)) if T(n) <= G(n) * C.
I\'m solving some recurrence relation problems for Big O and so far up till this point have only encountered recurrence relations that involved this form:
This question already has answers here: Closed 12 years ago. Possible Duplicate: Are there any O(1/n) algorithms?
What\'s the correct big O notation for an algorithm that runs in triangular time? Here\'s an example:
Think the title describes my thoughts pretty well :) I\'ve seen a lot of people lately that swear to LINQ, and while I also believe it\'s awesome, I also think you shouldn\'t be confused about the fa
Binary search has a average case performance as O(log n) and Quick Sort with O(n log n) is O(n log n开发者_如何学C) is same as O(n) + O(log n)Imagine a database with with every person in the world. Th
public void foo(int n, int m) { int i = m; while (i > 100) { i = i / 3; } for (int k = i ; k >= 0; k--) {
I have this method: public static int what(String str, char start, char end) { int count=0; for(int i=0;i<str.length(); i++) {
You have an array size n and a constant k (whatever) You can assume the the array is of int type (although it could be of any type)
I\'m still learning about complexity measurement using the Big O Notation, was wondering if I\'m correct to say that following method\'s complexity is O(n*log4n), where the \"4\" is a subscript.
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