// a) int sum = 0; for (int i = 1; i <= N + 2; i++) { sum++; } for (int j = 1; j <= N ⋆ 2; j++) { sum += 5; } cout << sum << endl; // b) int sum = 0; for (int i = 1; i <= N 5; i++) { for (int j = 1; j <= N 5; j+= 2) { sum++; } } cout << sum << endl; answer: answer:
// a) int sum = 0; for (int i = 1; i <= N + 2; i++) { sum++; } for (int j = 1; j <= N ⋆ 2; j++) { sum += 5; } cout << sum << endl; // b) int sum = 0; for (int i = 1; i <= N 5; i++) { for (int j = 1; j <= N 5; j+= 2) { sum++; } } cout << sum << endl; answer: answer:
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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Question
Give a tight bound of the nearest runtime complexity class for each of the following code fragments 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 ^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).
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In this question, it is asked to calculate the Big-Oh notation for the following code segments.
The exponential complexity must be defined with ^.
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