(1) Show, using either definition, that f(n) = n is O(nlog n). (2) In class, we saw that Big-O multiplies naturally. You will explore this more formally here. Prove the following statement mathematically (i.e. using proof techniques learned in Discrete Math): Proposition: If d(n) is O(f(n)) and e(n) is O(g(n)), then the product d(n)e(n) is O(f(n)g(n)). (3) There is a function void fnE(int i, int num) that runs in 1000-i steps, regardless of what num is. Consider the following code snippet: void fnA(int S[]) { int n = S.length; for (int i=0;i

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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(1) Show, using either definition, that f(n) = n is O(nlogn).
(2) In class, we saw that Big-0 multiplies naturally. You will explore this more formally here. Prove
the following statement mathematically (i.e. using proof techniques learned in Discrete Math):
Proposition: If d(n) is O(f(n)) and e(n) is 0(g (n)), then the product d(n)e(n) is
Olf(n)g(n)).
(3) There is a function void fnE(int i, int num) that runs in 1000-i steps, regardless of what
num is. Consider the following code snippet:
void fnA(int S[]) {
int n =
S.length;
for (int i=0;i<n;i++) {
fnE(i, S[i]);
}
}
What's the running time in Big-O of fnA as a function of n, which is the length of the array S. You
should assume that it takes constant time to determine the length of an array.
(4) Show that h(n) = 16n² + 1lnt +0.1nº is not O(n*).
Transcribed Image Text:(1) Show, using either definition, that f(n) = n is O(nlogn). (2) In class, we saw that Big-0 multiplies naturally. You will explore this more formally here. Prove the following statement mathematically (i.e. using proof techniques learned in Discrete Math): Proposition: If d(n) is O(f(n)) and e(n) is 0(g (n)), then the product d(n)e(n) is Olf(n)g(n)). (3) There is a function void fnE(int i, int num) that runs in 1000-i steps, regardless of what num is. Consider the following code snippet: void fnA(int S[]) { int n = S.length; for (int i=0;i<n;i++) { fnE(i, S[i]); } } What's the running time in Big-O of fnA as a function of n, which is the length of the array S. You should assume that it takes constant time to determine the length of an array. (4) Show that h(n) = 16n² + 1lnt +0.1nº is not O(n*).
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