Consider array A of n numbers. We want to design a dynamic programming algorithm to find the maximum sum of consecutive numbers with at least one number. Clearly, if all numbers are positive, the maximum will be the sum of all the numbers. On the other hand, if all of them are negative, the maximum will be the largest negative number. The complexity of your dynamic programming algorithm must be O(n²). However, the running time of the most efficient algorithm is O(n). Design the most efficient algorithm you can and answer the following questions based on it. To get the full points you should design the O(n) algorithm. However, if you cannot do that, still answer the following questions based on your algorithm and you will get partial credit.

C++ Programming: From Problem Analysis to Program Design
8th Edition
ISBN:9781337102087
Author:D. S. Malik
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Chapter15: Recursion
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Consider array A of n numbers. We want to design a dynamic programming algorithm to find the
maximum sum of consecutive numbers with at least one number. Clearly, if all numbers are positive,
the maximum will be the sum of all the numbers. On the other hand, if all of them are negative, the
maximum will be the largest negative number.
The complexity of your dynamic programming algorithm must be O(n²). However, the running time
of the most efficient algorithm is O(n). Design the most efficient algorithm you can and answer the
following questions based on it.
To get the full points you should design the O(n) algorithm. However, if you cannot do that, still
answer the following questions based on your algorithm and you will get partial credit.
Transcribed Image Text:Consider array A of n numbers. We want to design a dynamic programming algorithm to find the maximum sum of consecutive numbers with at least one number. Clearly, if all numbers are positive, the maximum will be the sum of all the numbers. On the other hand, if all of them are negative, the maximum will be the largest negative number. The complexity of your dynamic programming algorithm must be O(n²). However, the running time of the most efficient algorithm is O(n). Design the most efficient algorithm you can and answer the following questions based on it. To get the full points you should design the O(n) algorithm. However, if you cannot do that, still answer the following questions based on your algorithm and you will get partial credit.
(b)
compute the optimal solution of a problem?
What is the complexity of the numbers of subproblems that you solve/consider to
In your dynamic programming algorithm, what array/data structure you would use to
(c)
store the solutions of the subproblems, and what is its size/dimension(s)?
6.
Transcribed Image Text:(b) compute the optimal solution of a problem? What is the complexity of the numbers of subproblems that you solve/consider to In your dynamic programming algorithm, what array/data structure you would use to (c) store the solutions of the subproblems, and what is its size/dimension(s)? 6.
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