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14.10 Under what circumstances would the merge sort be preferred over the other two O(n lg n) sorting algorithms 14.11 Under what circumstances is the quick sort like the selection sort 14.12 Under what circumstances would the quick sort be preferred over the other two O(n lg n) sorting algorithms 14.13 How is the heap sort similar to the selection sort and the insertion sort 14.14 Which algorithm does the Java API use to implement its java.util.Arrays.sort() methods 14.15 A sorting algorithm is said to be stable if it preserves the order of equal elements. Which of the sorting algorithms are not stable 14.16 Which of the nine sorting algorithms outlined in this chapter require extra array space 14.17 Which of the nine sorting algorithms outlined in this chapter would work best on an external file of records 14.18 The merge sort is parallelizable. This means that parts of it can be performed simultaneously, independent of each other, provided that the computer has multiple processors that can run in parallel. This works for the merge sort because several different parts of the array can be subdivided or merged independently of other parts. Which of the other sorting algorithms described in this chapter are parallelizable

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CHAP. 14]

In previous chapters, we saw that the market demand curve for a commodity is derived by adding the individual s demand curves for the commodity. We also saw that each individual s (and thus the market) demand curve for a commodity is downwardsloping because of the substitution and income effects. However, an individual demands a particular commodity because of the satisfaction, or utility, he or she re-

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14.19 Imagine a Web site that has a Java applet for each sorting algorithm that shows how the algorithm works by displaying an animation of a test run on an array a[] of 256 random numbers in the range 0.0 to 1.0. The animation shows on each iteration of the algorithm s main loop a two-dimensional plot of 256 points (x, y), one for each element in the array, where x = i+1 and y = a[i]. Each plot in Figure 14.7 shows the progress halfway through the sort for one of the following six algorithms: selection sort insertion sort merge sort quick sort heap sort radix sort Match each plot with the sorting algorithm that produced it:

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14.1 If an O(n2) algorithm (e.g., the bubble sort, the selection sort, or the insertion sort) takes 3.1 milliseconds to run on an array of 200 elements, how long would you expect it to take to run on a similar array of: a. 400 elements b. 40,000 elements If an O(n lg n) algorithm (e.g., the merge sort, the quick sort, or the heap sort) takes 3.1 milliseconds to run on an array of 200 elements, how long would you expect it to take to run on a similar array of 40,000 elements The insertion sort runs in linear time on an array that is already sorted. How does it do on an array that is sorted in reverse order

How does the bubble sort perform on: a. An array that is already sorted b. An array that is sorted in reverse order How does the selection sort perform on: a. An array that is already sorted b. An array that is sorted in reverse order How does the merge sort perform on: a. An array that is already sorted b. An array that is sorted in reverse order How does the quick sort perform on: a. An array that is already sorted b. An array that is sorted in reverse order How does the heap sort perform on: a. An array that is already sorted b. An array that is sorted in reverse order

The bubble sort, the selection sort, and the insertion sort are all O(n2) algorithms. Which is the fastest and which is the slowest among them

ceives from consuming it. The more units of a commodity the individual consumes per unit of time, the greater is the total utility he receives. Although total utility increases, the extra, or marginal, utility received from consuming each additional unit of the commodity decreases. This is referred to as the law of diminishing marginal utility. Example 11.1 For purposes of illustration, we assume in Table 11.1 that satisfaction can actually be measured in terms of units of utility called utils. The rst two columns of Table 11.1 give an individual s hypothetical total utility (TU) schedule from consuming various quantities of commodity X (say oranges) per unit of time. Table 11.1

14.10 The merge sort, the quick sort, and the heap sort are all O(n lg n) algorithms. Which is the fastest and which is the slowest among them 14.11 Trace by hand the sorting of this array

int a[] = { 44, 88, 55, 99, 66, 33, 22, 88, 77 }

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