Searching Algorithms Quiz
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Questions and Answers

What is the primary purpose of searching in data structures?

  • To find the location of a desired key element (correct)
  • To replace elements in a list
  • To eliminate duplicates in a list
  • To sort elements based on value

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

  • Bubble Sort
  • Hash Search
  • Binary Search
  • Linear Search (correct)

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

  • 1
  • -1 (correct)
  • N
  • 0

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

<p>n+1 comparisons (A)</p> Signup and view all the answers

Which data structures can be searched using linear search?

<p>Arrays (C)</p> Signup and view all the answers

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

<p>It requires the data to be sorted. (A)</p> Signup and view all the answers

Which of the following statements about linear search is true?

<p>It can have a best case of one comparison. (C)</p> Signup and view all the answers

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

<p>11 (A)</p> Signup and view all the answers

Flashcards

Searching

The process of finding the location of a specific data element within a data structure like an array, linked list, or tree.

Linear Search

A search algorithm that starts at the beginning of a data structure and examines each element one by one until the desired element is found or the end is reached.

Worst-Case Time Complexity of Linear Search

The maximum number of comparisons required to find a specific element in a data structure using linear search. It occurs when the desired element is the last element in the list or when the element is not present.

Average-Case Time Complexity of Linear Search

The average number of comparisons needed to find an element in a list using linear search. It's calculated by averaging the number of comparisons across all possible instances.

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Best-Case Time Complexity of Linear Search

The number of comparisons needed when the desired element is found at the first position in the list. Only one look is needed!

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Study Notes

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.
  • 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.
  • 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).

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Description

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.

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