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Exam 3: Searching, Sorting, and Complexity Analysis

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Question 21

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What should the missing code be in the following algorithm if the goal is to determine how many seconds the algorithm runs? start = time.time() MyCount = 1 For x in range(100) : MyCount *= x Elapsed = time.time() - < missing code >

A) myCount
B) elapsed
C) start
D) x

E) B) and D)
F) C) and D)

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Question 22

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In the first step of the quicksort, you begin by selecting the item at the list's midpoint.

A) True
B) False

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Question 23

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Which of the following is a method to estimate the efficiency of an algorithm that predicts the amount of work an algorithm performs regardless of the platform?

How many loops are found in a typical insertion sort?

In terms of complexity, what is the average case for an insertion sort?

The bubble sort has a complexity of O( n ²).

The sequential search algorithm does more work to find a target at the beginning of a list than at the end of the list.

In the following code, what is the algorithm's complexity? minIndex = 0 CurrentIndex = 1 While currentIndex < len(lyst) : If lyst[currentIndex] < lyst[minIndex]: MinIndex = currentIndex CurrentIndex += 1 Return minIndex

In a binary search of an ascending order list, where does the search algorithm begin the search?

A bubble sort always requires approximately n² comparisons.

What should the missing code be in the following insertion sort algorithm? i = 1 While i < len(myList) : ItemToInsert = myList[i] J = i - 1 While j >= 0: If itemToInsert < myList[j]: MyList[j + 1] = myList[j] J -= 1 Else: Break < missing code > I += 1

Which method of determining the efficiency of algorithms allows you to rate them independently of timings or instruction counts?

What is the best case performance of a sequential search?

Which type of algorithm is analogous to how many people organize playing cards in their hands?

Algorithms with linear behavior do more work than those with quadratic behavior.

In terms of complexity, what is the worst-case scenario for an insertion sort?

This bubble sort has the effect of bubbling the largest items to the end of the list.

In the average case, where many items in a list are out of order, an insertion sort is linear.

Using a binary search, a list of 1 million items requires only 20 comparisons.

How can the performance complexity of the following algorithm be described? For x in range(numIterations) : Value = value * x Print(value)