Database System Concepts
Database System Concepts
7th Edition
ISBN: 9780078022159
Author: Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher: McGraw-Hill Education
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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)
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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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