For each of the following pieces of code, state the time complexity in terms of n using asymptotic notation. You do not need to show your work. a) def f.1(n): total - 0 for i in range(n): for j in range (n**2): for k in range (n//4): total +- nax(i, j, k) return total b) def f_2(n): total - 0 for i in range (n): for j in range (n + i): total + max(i, j) return total

For each of the following pieces of code, state the time complexity in terms of n using asymptotic notation. You do not need to show your work. a) def f.1(n): total - 0 for i in range(n): for j in range (n**2): for k in range (n//4): total +- nax(i, j, k) return total b) def f_2(n): total - 0 for i in range (n): for j in range (n + i): total + max(i, j) return total

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

See similar textbooks

Similar questions

Determine the time complexity function of the program snippet below, the proof must be in detail step by step until you get the time complexity function. int f1(int n) {if (n <= 1) return n;return 2 * f1(n/2);}int f2(int n) {if (n <= 1) return n;return f2(n/2) + f2(n/2);}
What is the time complexity and Big O notation for each of the following code segments? for(i=0;i<n; i++){for(j=0;j<n;j*2){ Statement; }} f(n) =O(n) =
q4) Calculate the time complexity for the code below with steps in deriving the result, take one unit of time for each basic operation. int a, b, c; a=2; b=3; for(int i=0; i<n;i++) for(int j=0;j<n;j++) c = (a * i ) +( b * j); cout<<c; Data structures and algorithms
please answer with proper explanation and step by step. don't give Direct answer. Question: If an algorithm takes n^2 operations, and the computer can perform 100 billion operations per second, what is a reasonable estimate of how long it will take to sort 2 billion elements (assuming there is ample memory, the computer doesn't crash, etc.)? a. 1 second b. 1 minute c. 1 hour d. 1 day e. 1 month f. 1 year g. 1 decade h. 1 century
What is the time complexity and Big O notation for each of the following code segments? P=0;for(i=0; i<n; i=i*2){P++;}for(j=0;j<n;j*2){Statement;} f(n) =O(n) =
What is the time complexity and Big O notation for each of the following code segments? P = 0;for(i=0;i<n;i=i+2){P = P + 1;} f(n) =O(n) =
What is the time complexity and Big O notation for each of the following code segments? for(i=1;i*i<n; i++){Statement;} f(n) =O(n) =
Help with Time/space complexity. Would the time complexity be O(n^2) or O(n*m) ?
Answer i) Consider a set of n random numbers: i) Let us say, the n random numbers are sorted into ascending order. Discuss the complexity to search the largest number from the sorted numbers. Express the complexity using big-O notation; ii) Let us say, the n random numbers are sorted into descending order. Discuss the complexity to search the largest number from the sorted numbers. Express the complexity using big-O notation;
The two different algorithms that perform the same complexity process are called B and C. The total number of operations (operations) performed with algorithm B is 64n. The total number of operations performed with the C algorithm is 16 n ^ 2. Here is my question: Determine the problem size n0 where B is better than C for n> n0 please.
Analyze the run time of the following code fragments. Write the results of your analysis in Big-O notation. Assume a “big enough” value for N. (1) for (int x=0; x < n; x++) for (int y=0; y < n; y++) for (int z=0; z < n; z++) System.out.print(“*”); (2) for(int x=0; x < n; x++) for (int y=x; y < n; y++) System.out.print(“*”);
Please answer this, thanks! a. give the running time (Big-Oh) and the space complexity. b. implement the code in the language of your choice and give the running time for three values of N (N must be >; 5). c. Compare your analysis with the actual running times. (1) sum = 0;for( i = 0; i < n; ++i )++sum;