R-4.13 Give a big-Oh characterization, in terms of n, of the running time of the example5method shown in Code Fragment 4.12.36 /** Returns the number of times second array stores sum of prefix sums from first. */37 public static int example5(int[ ] first, int[ ] second) { // assume equal-length arraysint n = first.length, count = 0;// loop from 0 to n-1for (int i=0; i R-4.12 Give a big-Oh characterization, in terms of n, of the running time of the example4method shown in Code Fragment 4.12.26 /** Returns the sum of the prefix sums of given array. */27 public static int example4(int[] arr) {2829int n = arr.length, prefix = 0, total = 0;for (int j=0; j

In computer science, time complexity is a notion that quantifies how long an algorithm must compute…

R-4.12 Give a big-Oh characterization, in terms of n, of the running time of the example4 method shown in Code Fragment 4.12. 26 /** Returns the sum of the prefix sums of given array. */ 27 public static int example4(int[ ] arr) { 28 29 int n = arr.length, prefix = 0, total = 0; for (int j=0; j

R-4.12 Give a big-Oh characterization, in terms of n, of the running time of the example4 method shown in Code Fragment 4.12. 26 /** Returns the sum of the prefix sums of given array. */ 27 public static int example4(int[ ] arr) { 28 29 int n = arr.length, prefix = 0, total = 0; for (int j=0; j

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

R-4.13 Give a big-Oh characterization, in terms of n, of the running time of the example5
method shown in Code Fragment 4.12.
36 /** Returns the number of times second array stores sum of prefix sums from first. */
37 public static int example5(int[ ] first, int[ ] second) { // assume equal-length arrays
int n = first.length, count = 0;
// loop from 0 to n-1
for (int i=0; i<n; i++) {
int total = 0;
for (int j=0; j< n; j++)
for (int k=0; k <= j; k++)
total += first[k];
if (second[i] == total) count++;
36 37 38 39 40 =25445 46 47
41
43
}
return count;
47 }
// loop from 0 to n-1
// loop from 0 to j

R-4.12 Give a big-Oh characterization, in terms of n, of the running time of the example4
method shown in Code Fragment 4.12.
26 /** Returns the sum of the prefix sums of given array. */
27 public static int example4(int[] arr) {
28
29
int n = arr.length, prefix = 0, total = 0;
for (int j=0; j<n; j++) {
prefix + = arr[j];
30
31
total + = prefix;
32
33
34
35
}
return total;
}
// loop from 0 to n-1

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