Python Programming: An Introduction to Computer Science, 3rd Ed.
3rd Edition
ISBN: 9781590282755
Author: John Zelle
Publisher: Franklin, Beedle & Associates
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Expert Solution & Answer
Chapter 1, Problem 1TF
Program Description Answer
The computer science is not a study of computers.
Hence, the given statement is “False”.
Expert Solution & Answer
Explanation of Solution
Computer science:
- Computer science is also called as computing science or computational science.
- Computer science is the study of processes that interacts with data. The processes that interact with data can be represented using
programs . - The computer programs enable the usage of
algorithms to store, manipulate digital information. - The computer is an important tool in computer science but it is not itself the object of study.
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Students have asked these similar questions
Design a dynamic programming algorithm for the Longest Alternating Subsequence problem
described below:
Input: A sequence of n integers
Output: The length of the longest subsequence where the numbers alternate between being larger and
smaller than their predecessor
The algorithm must take O(n²) time. You must also write and explain the recurrence.
Example 1:
Input: [3, 5, 4, 1, 3, 6, 5, 7, 3, 4]
Output: 8 ([3, 5, 4, 6, 5, 7, 3, 4])
Example 2:
Input: [4,7,2,5,8, 3, 8, 0, 4, 7, 8]
Output: 8 ([4, 7, 2, 5, 3, 8, 0,4])
(Take your time with this for the subproblem for this one)
Design a dynamic programming algorithm for the Coin-change problem described below:
Input: An amount of money C and a set of n possible coin values with an unlimited supply of each
kind of coin.
Output: The smallest number of coins that add up to C exactly, or output that no such set exists.
The algorithm must take O(n C) time. You must also write and explain the recurrence.
Example 1:
Input: C24, Coin values = = [1, 5, 10, 25, 50]
Output: 6 (since 24 = 10+ 10+1+1 +1 + 1)
Example 2:
Input: C = 86, Coin values = [1, 5, 6, 23, 35, 46, 50]
Output: 2 (since 86 = 46+35+5)
Design a dynamic programming algorithm for the Longest Common Subsequence problem de-
scribed below
Input: Two strings x = x1x2 xm and y = Y1Y2... Yn
Output: The length of the longest subsequence that is common to both x and y.
.
The algorithm must take O(m n) time. You must also write and explain the recurrence.
(I want the largest k such that there are 1 ≤ i₁ < ... < ik ≤ m and 1 ≤ j₁ < ... < jk ≤ n such that
Xi₁ Xi2 Xik = Yj1Yj2 ··· Yjk)
Example 1:
Input: x = 'abcdefghijklmnopqrst' and y = 'ygrhnodsh ftw'
Output: 6 ('ghnost' is the longest common subsequence to both strings)
Example 2:
Input: x = 'ahshku' and y = ‘asu'
Output: 3 ('asu' is the longest common subsequence to both strings)
Chapter 1 Solutions
Python Programming: An Introduction to Computer Science, 3rd Ed.
Ch. 1 - Prob. 1TFCh. 1 - Prob. 2TFCh. 1 - Prob. 3TFCh. 1 - Prob. 4TFCh. 1 - Prob. 5TFCh. 1 - Prob. 6TFCh. 1 - Prob. 7TFCh. 1 - Prob. 8TFCh. 1 - Prob. 9TFCh. 1 - Prob. 10TF
Ch. 1 - Prob. 1MCCh. 1 - Prob. 2MCCh. 1 - Prob. 3MCCh. 1 - Prob. 4MCCh. 1 - Prob. 5MCCh. 1 - Prob. 6MCCh. 1 - Prob. 7MCCh. 1 - Prob. 8MCCh. 1 - Prob. 9MCCh. 1 - Prob. 10MCCh. 1 - Prob. 1DCh. 1 - Prob. 2DCh. 1 - Prob. 3DCh. 1 - Prob. 4DCh. 1 - Prob. 5DCh. 1 - Prob. 1PECh. 1 - Prob. 2PECh. 1 - Prob. 3PECh. 1 - Prob. 4PECh. 1 - Prob. 5PECh. 1 - Prob. 7PE
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