In Computer Science, it is very important for Computer Scientists to know how to calculate the running times of algorithms in order to optimize code. For you Computer Scientists, I pose a question.
I got a theoretical question, will appreciate if you advise me here. Say, we have these two pieces of code.
Analysis of PSRS (Parallel sorting by regular sampling) In Computation part. Why Big-o of Sorting regular samples :
How do I go about finding the running time (in Big-O notati开发者_如何学Goon) of the basic algorithm that performs (y − 1) multiplications by x to find x^y?
Suppose you\'ve got a single linked list of size N, and you want to perform an operation on every element, beginning at the end.
Suppose I have the following : T(n) = 5n^2 +2n The asymtotic tight bound of this is theta n^2. I want to understand the reason behind dropping the 5. I understand why we开发者_运维知识库 ignore the lo
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I came across a question like this F(1) = 1 F(2n) = F(n) F(2n+1) = F(n) + F(n+1) Develop a recursive program to compute F
one month ago I\'ve been interviewed by some google PTO members. One of the questions was: Invert a string recursively in js and explain the running time by big O notation
If you scroll 2/3 of t开发者_StackOverflow社区he way down this article, it refers to O(1).Can someone explain what this means? This is called "Big O" notation.It tells you how efficient an a
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