What Is Searching and Its Types in Data Structure?


Heather Bennett

What Is Searching and Its Types in Data Structure?

Searching is the process of finding a specific element or value in a collection of data. In the field of data structure, searching plays a vital role in efficiently retrieving information from various data structures. There are several different types of searching algorithms that are commonly used, depending on the nature of the data and the requirements of the application.

Linear Search

Linear search, also known as sequential search, is the simplest and most basic type of search algorithm. It works by iterating through each element in a collection until the desired element is found or the end of the collection is reached.

To perform a linear search:

  • Start at the beginning of the collection.
  • Compare each element with the Target value.
  • If a match is found, return its index.
  • If no match is found after checking all elements, return a special value (often -1) to indicate that the Target value is not present in the collection.

Binary Search

Binary search is an efficient searching algorithm that requires a sorted collection. It works by repeatedly dividing the search space in half until it finds the desired element or determines that it does not exist in the collection.

To perform a binary search:

  • Start with defining low and high indices to represent the search space (usually 0 and n-1).
  • Calculate the middle index as (low + high) / 2.
  • If the middle element matches with the Target value, return its index.
  • If the middle element is greater than the Target value, update the high index to be one less than the middle index.
  • If the middle element is less than the Target value, update the low index to be one more than the middle index.
  • Repeat steps 2-5 until either the Target value is found or the low index becomes greater than the high index.


Hashing is a search technique that utilizes a hash function to map keys to their corresponding values in a data structure called a hash table. It provides constant-time average case search complexity, making it highly efficient for large datasets.

The process of searching using hashing involves:

  • Applying the hash function to compute an index for the given key.
  • Accessing the corresponding location in the hash table and checking if it contains the desired value.
  • If there is a match, return its location or value.
  • If there is no match, handle collisions (if any) according to a predefined collision resolution strategy (e.g., chaining or open addressing).


In summary, searching is an essential operation in data structures that allows us to locate specific elements efficiently. The choice of searching algorithm depends on factors such as data organization, time complexity requirements, and available resources.

Linear search works well for small collections or unsorted data, while binary search and hashing are more suitable for sorted collections and large datasets respectively. Understanding these different types of searching algorithms will help you optimize your code and improve overall performance in various applications.

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