181272 17 18 19 20 23 24 /** Returns the sum of the prefix sums of given array. */ public static int example3(int[] arr) { arr.length, total = 0; int n = } for (int j=0; j

Database System Concepts
7th Edition
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Chapter1: Introduction
Section: Chapter Questions
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R-4.11 Give a big-Oh characterization, in terms of n, of the running time of the example3
method shown in Code Fragment 4.12.
Transcribed Image Text:R-4.11 Give a big-Oh characterization, in terms of n, of the running time of the example3 method shown in Code Fragment 4.12.
17 ** Returns the sum of the prefix sums of given array. *
18 public static int example3(int[] arr) {
19
int n = arr.length, total
for (int j=0; j<n; j++)
20
21
for (int k=0; k <= j; k++)
total += arr[j];
return total;
222
23
24 }
=
0;
// loop from 0 to n-1
// loop from 0 to j
Transcribed Image Text:17 ** Returns the sum of the prefix sums of given array. * 18 public static int example3(int[] arr) { 19 int n = arr.length, total for (int j=0; j<n; j++) 20 21 for (int k=0; k <= j; k++) total += arr[j]; return total; 222 23 24 } = 0; // loop from 0 to n-1 // loop from 0 to j
Expert Solution
Step 1

Big-oh characterization:

It is one of the types of asymptotic notation, it is being used to calculate time complexity for any algorithm.

the equation used to represent this is:

fn=O gnfnc.gnc>0nkk0

where c is the constant,

Here we take it in the upper boundAt most for the worst case.

 

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