Python Programming: An Introduction to Computer Science, 3rd Ed.
3rd Edition
ISBN: 9781590282755
Author: John Zelle
Publisher: Franklin, Beedle & Associates
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Chapter 13, Problem 5MC
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The recursive function for Fibonacci function is inefficient because of the function does many repeated computations.
Hence, the correct answer is option “A”.
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The recursive Fibonacci function is inefficient becausea) it does many repeated computationsb) recursion is inherently inefficient compared to iterationc) calculating Fibonacci numbers is intractabled) fibbing is morally wrong
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7. The recursive procedure for solving the Towers of Hanoi can only be used if the number of discs parameter is 7 or less.
Recursion can be direct or indirect. It is direct when a function calls itself and it is indirect recursion when a function calls another function that then calls the first function. To illustrate solving a problem using recursion, consider the Fibonacci series: - 1,1,2,3,5,8,13,21,34...The way to solve this problem is to examine the series carefully. The first two numbers are 1. Each subsequent number is the sum of the previous two numbers. Thus, the seventh number is the sum of the sixth and fifth numbers. More generally, the nth number is the sum of n - 2 and n - 1, as long as n > 2.Recursive functions need a stop condition. Something must happen to cause the program to stop recursing, or it will never end. In the Fibonacci series, n < 3 is a stop condition. The algorithm to use is this:
1. Ask the user for a position in the series.2. Call the fib () function with that position, passing in the value the user entered.3. The fib () function examines the argument (n). If n < 3…
Chapter 13 Solutions
Python Programming: An Introduction to Computer Science, 3rd Ed.
Ch. 13 - Prob. 1TFCh. 13 - Prob. 2TFCh. 13 - Prob. 3TFCh. 13 - Prob. 4TFCh. 13 - Prob. 5TFCh. 13 - Prob. 6TFCh. 13 - Prob. 7TFCh. 13 - Prob. 8TFCh. 13 - Prob. 9TFCh. 13 - Prob. 10TF
Ch. 13 - Prob. 1MCCh. 13 - Prob. 2MCCh. 13 - Prob. 3MCCh. 13 - Prob. 4MCCh. 13 - Prob. 5MCCh. 13 - Prob. 6MCCh. 13 - Prob. 7MCCh. 13 - Prob. 8MCCh. 13 - Prob. 9MCCh. 13 - Prob. 10MCCh. 13 - Prob. 1DCh. 13 - Prob. 2DCh. 13 - Prob. 3DCh. 13 - Prob. 4DCh. 13 - Prob. 5DCh. 13 - Prob. 1PECh. 13 - Prob. 2PECh. 13 - Prob. 3PECh. 13 - Prob. 4PECh. 13 - Prob. 5PECh. 13 - Prob. 6PECh. 13 - Prob. 7PE
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- Question-3 There are n number of students in a class. Assume a teacher enters and wants to shake hand according to an algorithm: Algorithm (X) à 2n a) Write a recursive function to solve this problem for any number of students also calculate the time complexity of your code, along with an idea what might be the best technique to solve this problem other than recursion.arrow_forwardUse back substitution method to compute the following recursive function. Note that final results must be presented as a function of n. Show at least three substitutions before moving to k steps to get credit.arrow_forwardArtificial Intelligence (Part - 2) ==================== The Towers of Hanoi is a famous problem for studying recursion incomputer science and searching in artificial intelligence. We start with N discs of varying sizes on a peg (stacked in order according to size), and two empty pegs. We are allowed to move a disc from one peg to another, but we are never allowed to move a larger disc on top of a smaller disc. The goal is to move all the discs to the rightmost peg (see figure). To solve the problem by using search methods, we need first formulate the problem. Supposing there are K pegs and N disk. (2) What is the size of the state space?arrow_forward
- 8 T OR F The base case does not exist or is not reached, when there is infinite recursion.arrow_forwardThe first examples of recursion are the mathematical functions factorial and fibonacci. These functions are defined for non-negative integers using the following recursive formulas:factorial(0) = 1factorial(N) = N*factorial(N-1) for N > 0fibonacci(0) = 1fibonacci(1) = 1fibonacci(N) = fibonacci(N-1) + fibonacci(N-2) for N > 1Write recursive functions to compute factorial(N) and fibonacci(N) for a given non-negative integer N, and write a main() routine to test your functions.(In fact, factorial and fibonacci are really not very good examples of recursion, since the most natural way to compute them is to use simple for loops. Furthermore, fibonacci is a particularly bad example, since the natural recursive approach to computing this function is extremely inefficient.)arrow_forwardNeed python help. For problems 1 and 2, add your code to the file Lab2.java. Add your tests in the main function of Lab2.java. Do not use static variables in class Lab2 to implement recursive methods. Problem 1: Implement a recursive method min that accepts an array and returns the minimum element in the array. The recursive step should divide the array into two halves and find the minimum in each half. The program should run in O(n) time and consume O(logn) memory. Demonstrate the output of min on the array int [] a = { 2, 3, 5, 7, 11, 13, 17, 19, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 23, 29, 31, 37, 41, 43 } Problem 2 You have been offered a job that pays as follows: On the first day, you are paid 1 cent, on the second day, 2 cents, on the third day, 4 cents and so on. In other words, your pay doubles every day. Write a recursive method computePay that for a given day number computes the pay in cents. Assume that you accumulate all the money that you are paid. Write a…arrow_forward
- Artificial Intelligence (Part - 1) ==================== The Towers of Hanoi is a famous problem for studying recursion in computer science and searching in artificial intelligence. We start with N discs of varying sizes on a peg (stacked in order according to size), and two empty pegs. We are allowed to move a disc from one peg to another, but we are never allowed to move a larger disc on top of a smaller disc. The goal is to move all the discs to the rightmost peg (see figure). To solve the problem by using search methods, we need first formulate the problem. Supposing there are K pegs and N disk. (1) Propose a state representation for the problem?arrow_forwardQuestion-3 There are n number of students in a class.Assume a teacher enters and wants to shake hand according to an algorithm: Algorithm (X) à 2n a) Write a recursive function to solve this problem for any number of students also calculate the time complexity of your code, along with an idea what might be the best technique to solve this problem other than recursion. b) Consider this Algorithm-Z , Taking list of integer as input List Of Integer: X(Integer: number) List Of Integer: Y Integer: i = 2 While (i< number) While (number Mod i == 0) Y.Add(i) number = number / i End While i = i + 1 End While If (number > 1) Then Y.Add(number) Return Y End X (i) Explain what Algorithm Z is doing? (ii) Analyze the complexity of Algo-Z and then write an algorithm Better-Algo-X that does exactly the same thing but with a strictly better time complexityarrow_forwardQuestion-3 There are n number of students in a class. Assume a teacher enters and wants to shake hand according to an algorithm: Algorithm (X) à 2n a) Write a recursive function to solve this problem for any number of students also calculate the time complexity of your code, along with an idea what might be the best technique to solve this problem other than recursion. b) Consider this Algorithm-Z , Taking list of integer as input List Of Integer: X(Integer: number) List Of Integer: Y Integer: i = 2 While (i < number) While (number Mod i == 0) Y.Add(i) number = number / i End While i = i + 1 End While If (number > 1) Then Y.Add(number) Return Y End X (i) Explain what Algorithm Z is doing? (ii) Analyze the complexity of Algo-Z and then write an algorithm Better-Algo-X that does exactly the same thing but with a strictly better time complexityarrow_forward
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