Flashcards on Bubble sort

Bubble Sort Explained: Algorithm, Complexity & Examples

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What is the primary goal of sorting in computer science?

The goal of sorting is to make data easier to search, analyze, and process.

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Bubble Sort

42 cards

Card 1

Question: What is the primary goal of sorting in computer science?

Answer: The goal of sorting is to make data easier to search, analyze, and process.

Card 2

Question: How does Bubble Sort work?

Answer: Bubble Sort repeatedly steps through the list, compares adjacent elements, and swaps them if they are in the wrong order, repeating until no swaps are

Card 3

Question: Where does the name "Bubble Sort" come from?

Answer: The name "Bubble Sort" comes from the way smaller or larger elements "bubble" to their correct positions, much like bubbles rising to the surface of w

Card 4

Question: In Bubble Sort, after the first complete pass through a list sorted in ascending order, what element is guaranteed to be in its correct position?

Answer: After the first complete pass, the largest element will have "bubbled up" to its correct position at the end of the list.

Card 5

Question: How many passes does Bubble Sort require in the worst case for a list of length 'n'?

Answer: The algorithm requires n-1 passes in the worst case.

Card 6

Question: What is the purpose of the outer loop in Bubble Sort?

Answer: The outer loop aims to place one element into its final sorted position with each pass.

Card 7

Question: What is the purpose of the inner loop in Bubble Sort?

Answer: The inner loop iterates through the unsorted portion of the list, comparing and potentially swapping adjacent elements.

Card 8

Question: For a list of length 'n', up to what index does the inner loop compare elements in pass 'i'?

Answer: In pass 'i', the inner loop compares elements from index j = 0 up to n-2-i.

Card 9

Question: Why does the inner loop's comparison range decrease with each pass 'i' in Bubble Sort?

Answer: The last 'i' elements are already in their sorted positions and do not need to be compared again.

Card 10

Question: What notation is typically used to describe algorithm efficiency?

Answer: Algorithm complexity is typically described using Big O notation.