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Exercise 100 Points Following Three Code Snippets Corresponding Python Code List Appendix Q43907894

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Exercise I (100 points) For each of the following three code snippets (corresponding Python code is list in the Appendix at t

Exercise I (100 points) For each of the following three code snippets (corresponding Python code is list in the Appendix at the end of this assignment): a. Calculate the theoretical time complexity by counting the number of subtractions as basic operation. What do you think is the Big-Oh for the complexity? Prove how did you get the big-Oh only for part 1. b. Plot a graph of the theoretical time complexity. c. Implement the code in the language of your choice, and find the running time for several values of n (for instance, for n= 1000, 2000, 300l.10000) and plot the results. (make sure not to have other applications running in the background. You can use different values for n as you see fit) d. Using the two plotted graphs, comment on the growth rate of the theoretical time complexity in comparison with the actual running times. Negative Sum = 0; for (i = 1; i <= n; i++) Negative Sum = Negative Sum – i -1; N Negative 3Sum = 0; for (i = 1; i <= 3*n+2; i++) Negative 3 Sum = Negative 3Sum – i; NegativeSubsum = 0; for (i = 1; i <= 2*n; i++) for (j = 1; j <= i+1; i++) Negative SubSum = Negative SubSum- j + 1; Waumini waumu Show transcribed image text Exercise I (100 points) For each of the following three code snippets (corresponding Python code is list in the Appendix at the end of this assignment): a. Calculate the theoretical time complexity by counting the number of subtractions as basic operation. What do you think is the Big-Oh for the complexity? Prove how did you get the big-Oh only for part 1. b. Plot a graph of the theoretical time complexity. c. Implement the code in the language of your choice, and find the running time for several values of n (for instance, for n= 1000, 2000, 300l.10000) and plot the results. (make sure not to have other applications running in the background. You can use different values for n as you see fit) d. Using the two plotted graphs, comment on the growth rate of the theoretical time complexity in comparison with the actual running times. Negative Sum = 0; for (i = 1; i

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Answer to Exercise I (100 points) For each of the following three code snippets (corresponding Python code is list in the Appendix…

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