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(a) A short description of your algorithm, where you explain the dynamic programing approach (see the sketch of the Algorithm below). More precisely, you need to indicate how you compute d[0] (this is the initialization step), and how you compute for every i ≥ 1, the value of d[i] using the values of some of the previous d[j]'s, for j

(a) A short description of your algorithm, where you explain the dynamic programing approach (see the sketch of the Algorithm below). More precisely, you need to indicate how you compute d[0] (this is the initialization step), and how you compute for every i ≥ 1, the value of d[i] using the values of some of the previous d[j]'s, for j

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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(a) A short description of your algorithm, where you explain the dynamic programing approach (see the sketch of the Algorithm below). More precisely, you need to indicate how you compute d[0] (this is the initialization step), and how you compute for every i ≥ 1, the value of d[i] using the values of some of the previous d[j]'s, for j <i). (b) A table with the results your program gives for the three data sets given below. (c) The java code (so that the grader can make observations).
Transcribed Image Text:(a) A short description of your algorithm, where you explain the dynamic programing approach (see the sketch of the Algorithm below). More precisely, you need to indicate how you compute d[0] (this is the initialization step), and how you compute for every i ≥ 1, the value of d[i] using the values of some of the previous d[j]'s, for j <i). (b) A table with the results your program gives for the three data sets given below. (c) The java code (so that the grader can make observations).
Example: Input: 10, 9, 2, 5, 3, 101, 7, 18. Output: 4, or for the bonus solution 4, (2, 5, 7, 18). Test your program on the following sequences and insert to the first file that you submit screenshots with the computer screen showing the results for each sequence: • 10, 9, 2, 5, 3, 101, 7, 18 • 186, 359, 274, 927, 890, 520, 571, 310, 916, 798, 732, 23, 196, 579, 426,188, 524, 991, 91, 150, 117, 565, 993, 615, 48, 811, 594, 303, 191, 505, 724, 818, 536, 416, 179, 485, 334, 74, 998, 100, 197, 768, 421, 114, 739, 636, 356, 908, 477, 656 • 318, 536, 390, 598, 602, 408, 254, 868, 379, 565, 206, 619, 936, 195, 123, 314, 729, 608, 148, 540, 256, 768, 404, 190, 559, 1000, 482, 141, 26, 230, 550, 881, 759, 122, 878, 350, 756, 82, 562, 897, 508, 853, 317, 380, 807, 23, 506, 98, 757, 247
Transcribed Image Text:Example: Input: 10, 9, 2, 5, 3, 101, 7, 18. Output: 4, or for the bonus solution 4, (2, 5, 7, 18). Test your program on the following sequences and insert to the first file that you submit screenshots with the computer screen showing the results for each sequence: • 10, 9, 2, 5, 3, 101, 7, 18 • 186, 359, 274, 927, 890, 520, 571, 310, 916, 798, 732, 23, 196, 579, 426,188, 524, 991, 91, 150, 117, 565, 993, 615, 48, 811, 594, 303, 191, 505, 724, 818, 536, 416, 179, 485, 334, 74, 998, 100, 197, 768, 421, 114, 739, 636, 356, 908, 477, 656 • 318, 536, 390, 598, 602, 408, 254, 868, 379, 565, 206, 619, 936, 195, 123, 314, 729, 608, 148, 540, 256, 768, 404, 190, 559, 1000, 482, 141, 26, 230, 550, 881, 759, 122, 878, 350, 756, 82, 562, 897, 508, 853, 317, 380, 807, 23, 506, 98, 757, 247
Expert Solution
Step 1 : Short description for how the algorithm worked
 In the dp array, we store the length of the longest increasing
        subsequence
        that ends at the current index. We initialize the dp array with 1, since the
        longest increasing subsequence that ends at the first index is 1.
        We then iterate through the array and for each index, we iterate through all
        the previous indices and check if the current element is greater than the
        previous element. If it is, we check if the length of the longest increasing
        subsequence that ends at the previous index is greater than the length of the
        longest increasing subsequence that ends at the current index. If it is, we
        update the length of the longest increasing subsequence that ends at the
        current index to be the length of the longest increasing subsequence that
        ends at the previous index plus 1.
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