What Are the Types of Searching in Data Structure?


Larry Thompson

Data structures are essential for efficient data storage and retrieval. One of the key operations performed on data structures is searching.

Searching involves finding a specific element or a set of elements within a given data structure. Different types of searching algorithms exist, each with its own advantages and disadvantages. In this article, we will explore some of the most commonly used types of searching in data structures.

Linear Search

The linear search is one of the simplest searching algorithms. It iterates through each element in the data structure sequentially until the desired element is found or the end of the structure is reached. It is commonly used for unsorted arrays or lists.


  1. Start at the beginning of the data structure.
  2. Compare each element with the desired element.
  3. If a match is found, return the index or position of the element.
  4. If no match is found after iterating through all elements, return a specified value to indicate that the element was not found.

Binary Search

The binary search algorithm works efficiently on sorted arrays or lists. It follows a divide-and-conquer approach by repeatedly dividing the search interval in half until the desired element is found.


  1. Start with two pointers, one pointing to the beginning and another to the end of the sorted array or list.
  2. Calculate the middle index as (start + end) / 2.
  3. If the middle element matches with the desired element, return its index.
  4. If the middle element is greater than the desired element, update the end pointer to (middle – 1) and repeat from step 2.
  5. If the middle element is smaller than the desired element, update the start pointer to (middle + 1) and repeat from step 2.
  6. If no match is found after the pointers converge, return a specified value to indicate that the element was not found.


Hashing is a technique used to map data elements to a fixed-size array called a hash table. It provides constant-time average case complexity for searching, making it highly efficient.


  1. Create a hash table with a fixed number of slots or buckets.
  2. Apply a hash function to calculate the index or position where the element should be stored in the hash table.
  3. If there is no collision (two elements mapping to the same index), insert the element at that position.
  4. If there is a collision, handle it using techniques such as chaining or open addressing.
  5. To search for an element, apply the same hash function and retrieve its value from the corresponding position in the hash table.

These are just some of the types of searching algorithms used in data structures. Each algorithm has its own strengths and weaknesses, and their suitability depends on factors such as data size, search frequency, and memory constraints. It’s important to understand these algorithms to make informed decisions when implementing data structures in various applications.

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