Searching Algorithms Quiz

What is the primary purpose of searching in data structures?

Which search algorithm requires checking every element one at a time until the desired key is found?

What value is returned by a linear search if the desired key is not found?

In terms of time complexity, what is the worst-case scenario for linear search?

Which data structures can be searched using linear search?

What is a key characteristic of binary search compared to linear search?

Which of the following statements about linear search is true?

If a linear search needs to examine each element in an array of size 10, how many maximum comparisons will it make?

Searching Algorithms

Searching involves finding a specific item within a collection of data.
The appropriate search algorithm depends on the data structure.
Two common search algorithms are linear search and binary search.

Linear Search

A sequential search method.
Starting at the beginning of the list, comparing each element to the desired key.
Continues until a match is found or the end of the list is reached.

Linear Search Example

Best-case time complexity: O(1) – The desired key is found at the first element.
Worst-case time complexity: O(n) – The desired key is found at the last position.
Average-case time complexity: O(n) – The average number of comparisons is proportional to the length of the list.

Binary Search

Effective only on sorted data.
Starts by comparing the key to the middle element.
If the target matches, the algorithm returns its location.
If the target is smaller, search continues in the lower half; otherwise, in the upper half.
Repeats the process until the key is found.
Halves the search space with each comparison.

Binary Search Example

Best-case time complexity: O(1) – Key is found at first comparison.
Worst-case time complexity: O(log n)
Average-case time complexity: O(log n) – Number of comparisons is proportional to log2(n).

Test your knowledge on searching algorithms, focusing on linear and binary search techniques. Understand their implementations, complexities, and when to use each method in data structures. Challenge yourself with various scenarios and examples.