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Pearson eText Technology In Action, Complete -- Instant Access (Pearson+)
16th Edition
ISBN: 9780136874522
Author: Alan Evans, Kendall Martin
Publisher: PEARSON+
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Chapter 6, Problem 1MC
Program Description Answer

Moore’s Law refers to the pace at which CPUs improve and also it refers to the number of transistors inside the CPU chip.

Therefore, the correct answer is option “D”.

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Explanation of Solution

Moore’s Law:

Moore’s Law is invented by the Intel executive Gordon Moore in the year of 1965.

  • Moore detected that each new processor chip carries almost double the capacity of the early day’s processor chip.
  • It refers to the number of transistors inside the CPU chip.
  • Each new processor chip will be released every two years or within 18 to 24 months of the invention of the previous chip.
  • Since, Moore’s predicts that the growth could cause power of computing will rise exponentially over the period of time for future estimation.

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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)
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