Introduction to Java Programming and Data Structures, Comprehensive Version (11th Edition)
11th Edition
ISBN: 9780134670942
Author: Y. Daniel Liang
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Videos
Textbook Question
Chapter 22.3, Problem 22.3.5CP
Example 7 in Section 22.3 assumes n = 2k. Revise the
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
What is the leading term for the following expressions and specify the lowest Big O Complexity for each algorithm?
Let A(n) = 3A(n/2) + n2 + 3n + 4.Using the MasterTheorem, the computational complexity is _______.
A.O(n2log n)
B.O(n1.58) where 1.58 = log23
C.O(n2)
D.O(n0.63) where 0,63 = log32
7. Suppose that you have two different algorithms for solving a problem. To solve a problem of size n, the first algorithm uses exactly n(log2 n) operations and the second algorithm uses exactly n3/2 operations. As n grows, which algorithm uses fewer operations?
Chapter 22 Solutions
Introduction to Java Programming and Data Structures, Comprehensive Version (11th Edition)
Ch. 22.2 - Prob. 22.2.1CPCh. 22.2 - What is the order of each of the following...Ch. 22.3 - Count the number of iterations in the following...Ch. 22.3 - How many stars are displayed in the following code...Ch. 22.3 - Prob. 22.3.3CPCh. 22.3 - Prob. 22.3.4CPCh. 22.3 - Example 7 in Section 22.3 assumes n = 2k. Revise...Ch. 22.4 - Prob. 22.4.1CPCh. 22.4 - Prob. 22.4.2CPCh. 22.4 - Prob. 22.4.3CP
Ch. 22.4 - Prob. 22.4.4CPCh. 22.4 - Prob. 22.4.5CPCh. 22.4 - Prob. 22.4.6CPCh. 22.5 - Prob. 22.5.1CPCh. 22.5 - Why is the recursive Fibonacci algorithm...Ch. 22.6 - Prob. 22.6.1CPCh. 22.7 - Prob. 22.7.1CPCh. 22.7 - Prob. 22.7.2CPCh. 22.8 - Prob. 22.8.1CPCh. 22.8 - What is the difference between divide-and-conquer...Ch. 22.8 - Prob. 22.8.3CPCh. 22.9 - Prob. 22.9.1CPCh. 22.9 - Prob. 22.9.2CPCh. 22.10 - Prob. 22.10.1CPCh. 22.10 - Prob. 22.10.2CPCh. 22.10 - Prob. 22.10.3CPCh. 22 - Program to display maximum consecutive...Ch. 22 - (Maximum increasingly ordered subsequence) Write a...Ch. 22 - (Pattern matching) Write an 0(n) time program that...Ch. 22 - (Pattern matching) Write a program that prompts...Ch. 22 - (Same-number subsequence) Write an O(n) time...Ch. 22 - (Execution time for GCD) Write a program that...Ch. 22 - (Geometry: gift-wrapping algorithm for finding a...Ch. 22 - (Geometry: Grahams algorithm for finding a convex...Ch. 22 - Prob. 22.13PECh. 22 - (Execution time for prime numbers) Write a program...Ch. 22 - (Geometry: noncrossed polygon) Write a program...Ch. 22 - (Linear search animation) Write a program that...Ch. 22 - (Binary search animation) Write a program that...Ch. 22 - (Find the smallest number) Write a method that...Ch. 22 - (Game: Sudoku) Revise Programming Exercise 22.21...Ch. 22 - (Bin packing with smallest object first) The bin...Ch. 22 - Prob. 22.27PE
Additional Engineering Textbook Solutions
Find more solutions based on key concepts
(Adapted from Barwise and Etchemendy (1993).) Given the following, can you prove that the unicorn is mythical? ...
Artificial Intelligence: A Modern Approach
Any piece of data that is stored in a computers memory must be stored as a binary number.
Starting Out with Programming Logic and Design (5th Edition) (What's New in Computer Science)
Add the following member function to the ADT class DigitalTime defined in Displays 12.1 and 12.2: void DigitalT...
Problem Solving with C++ (10th Edition)
Modify the temperature conversion program to print a heading above the table.
C Programming Language
Date Class Modification Modify the Date class in Programming Challenge 1 of Chapter 13. The new version should ...
Starting Out with C++ from Control Structures to Objects (8th Edition)
What is a local variable? How is access to a local variable restricted?
Starting Out with Python (3rd Edition)
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.Similar questions
- Reorder the following efficiencies from largest complexity to smallest complexity: nlog2(n) n+n2+n3 24 n1.5arrow_forwardFor relatively small values of n, algorithms with larger orders can be more efficient than algorithms with smaller orders. Use a graphing calculator or computer to answer this question. For what values of n is an algorithm that requires n operations more efficient than an algorithm that requires [50 log2(n)] operations? (Assume n is an integer such that n > 1.) n?arrow_forwardGive an example of an algorithm that is O(1), an algorithm that is O(n) and an algorithm that is O(n2). Discuss the difference between them.arrow_forward
- Consider the following recursive algorithm, where // denotes integer division: 3//2 = 1, 5//2 = 2, etc. H(n): if n <= 1: return H(n//2) for i from 0 to n print(min(3, i)) Let function T(n) denote the running time of this algorithm. Derive T(n) and prove its worst case time complexityarrow_forwardQ10. Consider the following algorithm: g1 = 7 g2 = 6 For k starting at 3 and ending with 8: gk = (k-1)·gk-1 + gk-2 What is the last term, g8, of the recursive sequence generated as a result of executing this algorithm?arrow_forwardComputer Science Write the PSEUDOCODE for an algorithm that takes as input a list of numbers that are sorted in nondecreasing order, and finds the location(s) of the most frequently occurring element(s) in the list. If there are more than one element that is the most frequently occurring, then return the locations of all of them. Analyze the worst-case time complexity of this algorithm and give the O() estimate. (A list is in nondecreasing order if each number in the list is greater than or equal to the number preceding it.)arrow_forward
- Please provide at least one example of an algorithm for each of the following complexity classes: log2n, n, n log2n, n2, n3, 2n, n!, Undecidable..arrow_forwardModeling the spread of a virus like COVID-19 using recursion. Let N = total population (assumed constant, disregarding deaths, births, immigration, and emigration). S n = number who are susceptible to the disease at time n (n is in weeks). I n = number who are infected (and contagious) at time n. R n = number who are recovered (and not contagiuous) at time n. The total population is divided between these three groups: N = S n + I n + R n There are several hidden assumptions here that may or may not apply to COVID-19, such as a recovered person is assumed to not be able to get the disease a second time, at least within the time window being examined. On week 0 (the start), you assume a certain small number of people have the infection (just to get things going). Everyone else is initially susceptible, and no one is recovered. There are two constants of interest: Let period = time period that it takes for an infected person to recover (recover meaning they become not infectious to…arrow_forwardConsider a divide-and-conquer algorithm that calculates the sum of all elements in a set of n numbers by dividing the set into two sets of n/2 numbers each, finding the sum of each of the two subsets recursively, and then adding the result. What is the recurrence relation for the number of operations required for this algorithm? Answer is f(n) = 2 f(n/2) + 1. Please show why this is the case.arrow_forward
- For each, draw the recursion tree, find the height of the tree, the running time of each layer, and the sum of running times. Then use this info to find the explicit answer for T(n). a. T(n) = 2T(n/4) + √ n (n is a power of 4 (n = 4^k) for some positive integer k) b. T(n) = 9T(n/3) + n^2 (n is a power of 3 (n = 3^k) for some positive integer k) c. T(n) = T(n/2) + 1 (n is a power of 2 (n = 2^k) for some positive integer k)arrow_forwardThe travel time function of an algorithm has the form: f(n) = 3n^2+4n+8.a. Determine the values of c and n0, so that big-oh O(n^2) satisfies the rule f(n) <= cg(n); n≥n0,b. Show (picture) the graphs of f(n) and g(n).arrow_forwardAssume that each of the expressions below gives the processing time T(n) spent by an algorithm for solving a problem of size n. Select the dominant term(s) having the steepest increase in n and specify the lowest Big-Oh complexity of each algorithm. For example, the dominant term in 0.1n + 10n4 is 10n4 and it is O(n4). Expression Dominant term(s) O(. . .) 5 + 0.001n3 + 0.025n 500n + 100n1.5 + 50n log10 n 0.3n + 5n1.5 + 2.5 · n1.75 n2 log2 n + n(log2 n)2 n log3 n + n log2 n 100n + 0.01n2 0.01n + 100n2 2n + n0.5 + 0.5n1.25 0.01n log2 n + n(log2 n)2 100n log3 n + n3 + 100narrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Database System ConceptsComputer ScienceISBN:9780078022159Author:Abraham Silberschatz Professor, Henry F. Korth, S. SudarshanPublisher:McGraw-Hill Education
Starting Out with Python (4th Edition)Computer ScienceISBN:9780134444321Author:Tony GaddisPublisher:PEARSON
Digital Fundamentals (11th Edition)Computer ScienceISBN:9780132737968Author:Thomas L. FloydPublisher:PEARSON
C How to Program (8th Edition)Computer ScienceISBN:9780133976892Author:Paul J. Deitel, Harvey DeitelPublisher:PEARSON
Database Systems: Design, Implementation, & Manag...Computer ScienceISBN:9781337627900Author:Carlos Coronel, Steven MorrisPublisher:Cengage Learning
Programmable Logic ControllersComputer ScienceISBN:9780073373843Author:Frank D. PetruzellaPublisher:McGraw-Hill Education
Database System Concepts
Computer Science
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:McGraw-Hill Education
Starting Out with Python (4th Edition)
Computer Science
ISBN:9780134444321
Author:Tony Gaddis
Publisher:PEARSON
Digital Fundamentals (11th Edition)
Computer Science
ISBN:9780132737968
Author:Thomas L. Floyd
Publisher:PEARSON
C How to Program (8th Edition)
Computer Science
ISBN:9780133976892
Author:Paul J. Deitel, Harvey Deitel
Publisher:PEARSON
Database Systems: Design, Implementation, & Manag...
Computer Science
ISBN:9781337627900
Author:Carlos Coronel, Steven Morris
Publisher:Cengage Learning
Programmable Logic Controllers
Computer Science
ISBN:9780073373843
Author:Frank D. Petruzella
Publisher:McGraw-Hill Education
Introduction to Big O Notation and Time Complexity (Data Structures & Algorithms #7); Author: CS Dojo;https://www.youtube.com/watch?v=D6xkbGLQesk;License: Standard YouTube License, CC-BY