A Level CS Binary Search

What is the first step in implementing a binary search algorithm?

• Initializing variables with their starting states

• Sorting the dataset

• Calculating the midpoint of the dataset

• Entering a while loop

What must be true for a binary search to be performed?

• The data set must contain string values only

• The data set must be unsorted

• The data set must be divided into three parts

• The data set must be sorted

What does the binary search algorithm do after each iteration if the item is not found?

• It repeats the search on the entire dataset

• It stops the search

• It discards half of the dataset

• It adds more data to the dataset

Which variable is used to indicate whether the item has been found in a binary search?

• first

• last

• midpoint

• found

How is the midpoint calculated in a binary search algorithm?

• By dividing the dataset into equal parts

• By subtracting the last index from the first

• By adding the first and last index and dividing by two

• By multiplying the first and last index

What happens if the item at the midpoint is less than the item being searched for?

• The search stops

• The first variable is adjusted to midpoint plus one

• The last variable is adjusted to midpoint plus one

• The first variable is adjusted to midpoint minus one

What is the condition for the while loop to continue executing in a binary search?

• found equals true

• first is greater than last

• The dataset is fully searched

• first is less than or equal to last and found equals false

In the provided Python code example, how is the list 'items' described?

• A list of user inputs

• A list of American states

• A list of numbers

• A list of binary numbers

What does the binary search algorithm do if the item is found?

• Exits the while loop

• Sets the 'found' variable to false

• Deletes the item from the dataset

• Continues to search the rest of the dataset

What is a key advantage of binary search over linear search?

• It requires the dataset to be unsorted

• It is less efficient for large datasets

• It quickly reduces the search range by half after each iteration

• It searches each item in the dataset one by one