Java Programming Big O question

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
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Java Programming Big O question

Give a tight bound of the nearest runtime complexity class for the following code fragment in Big-
Oh notation, in terms of the variable N. In other words, write the code's growth rate as N grows.
Write a simple expression that gives only a power of N using a caret a character for exponentiation,
such as o(N^2) to represent O(N2) or O(log N) to represent O(log2 N). Do not write an exact
calculation of the runtime such as O(2N3 + 4N + 14).
// a)
int sum = 0;
for (int i = e; i « N; i++) {
for (int j = 1; j< N; j=j*2) {
sum++;
for (int j
= 1; j <N + 5; j=j*2) {
for (int k = 1; k < 99999; k++) {
sum++;
printin(sum);
O O(N^2)
O O(N)
O O(Log N)
O O(N Log N)
Transcribed Image Text:Give a tight bound of the nearest runtime complexity class for the following code fragment in Big- Oh notation, in terms of the variable N. In other words, write the code's growth rate as N grows. Write a simple expression that gives only a power of N using a caret a character for exponentiation, such as o(N^2) to represent O(N2) or O(log N) to represent O(log2 N). Do not write an exact calculation of the runtime such as O(2N3 + 4N + 14). // a) int sum = 0; for (int i = e; i « N; i++) { for (int j = 1; j< N; j=j*2) { sum++; for (int j = 1; j <N + 5; j=j*2) { for (int k = 1; k < 99999; k++) { sum++; printin(sum); O O(N^2) O O(N) O O(Log N) O O(N Log N)
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