So a quick thought; Could one argue that O(∞) is actually O(1)? I mean it isn\'t depend on input size?
Considering the following code: for ( int j = 0; j < 2n; j++) { for ( int k = 0; k < n^3; k += 3) sum++;
Just wondering if HashSet.equals(anotherHashSet) runs in constant time (also with a ConcurrentHashSet as argument), which I\'m assuming it does for efficiency reasons. Can\'t see anything which mentio
There are N sets Ai to An each with string entries开发者_StackOverflow中文版. The average size of a set is K.
I have a Big O notation question. Say I have a Java program that does the following things: Read an Array of Integers into a HashMap that keeps track of how many occurrences of the Integers exists i
I\'m trying to understand this paper: Stable minimum space partitioning in linear time. It seems that a critical part of the claim is that
I\'ve seen the operation of copying a string describ开发者_如何学JAVAed as O(n), where n is the length of the string, because it\'s assumed that we need to iterate through each character of the string
the first problem; sum = 0; for i = 1 to n; i++ { for j = 1 to i * i; j++ { for k = 1 to j; k++ sum ++; } }
The function max() which returns the maximum element from a list . . . what is its running time开发者_运维问答 (in Python 3) in terms of Big O notation?It\'s O(n), since it must check every element.If
Is there an algorithmic approach to find the minimum of an unsorted array in logarithmic time ( O(logn) )? Or is it only possible in linear time? I don\'t want to go parallel.
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