Programming with Microsoft Visual Basic 2017
Programming with Microsoft Visual Basic 2017
8th Edition
ISBN: 9781337102124
Author: Diane Zak
Publisher: Cengage Learning
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Chapter 3, Problem 4MQ6
Program Plan Intro

Option Strict On:

The Option Strict On statement is used to prevent the data loss in the implicit type conversion.

  • If one data type value is converted to a narrower data type, then smaller number or number with fewer precision data loss is occurred in the implicit conversion.
    • For example,
    • Consider the statement Dim intValue As Integer = 18.36
      • Here, the double value is converted as integer number and stored into the memory location.
      • In the implicit conversion, the value is rounded off by the nearest whole number and the decimal portions are removed.
      • At the final result, the number is stored as 18, so the decimal part .36 is removed from the number. Here, the data loss has been occurred.
    • If the Option Strict is On, then it will not allow the implicit conversion; it raises a warning while the program tries to perform an implicit conversion.
  • When the Option Strict is on, it does not allow the following conversions:
    • String to number implicit conversion is not allowed.
    • Number to string implicit conversion is not allowed.
    • Wider data types to narrower data types implicit conversion is not allowed.
    • Implicitly narrower data types are promoted as wider data types.

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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)

Chapter 3 Solutions

Programming with Microsoft Visual Basic 2017

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