Linear Search in Data Structure

What is a Linear Search in Data Structure?

The simplest technique for finding an element in a data collection is to use a linear search. It checks each element until it finds a match, from the beginning to the end of the data collection. Once the target element has been found, the search is completed and ended.

Linear Search Algorithm

• Start with the first element.
• Compare the target to the current element.
• If the values match, return the index and terminate.
• If no match, proceed to the next element.
• Repeat until the target is identified or all components have been verified.

Linear Search Algorithm's Complexity Analysis

Time Complexity

Space Complexity

The space complexity of linear search is constant, i.e. O(1), because no important additional memory is used.

When should you use a linear search?

• Small Data Sets: Suitable for small datasets with a few items.
• Unsorted Data: Operates effectively with unsorted or unordered data, checking each element progressively.
• Singly Linked Lists: When direct access is not possible, nodes are traversed one at a time.
• Infrequent Searches: Ideal for infrequent searches or static lists; easy to implement with minimum setup.
• Educational Purposes: Basic search concepts are presented using an introductory algorithm in programming and computer science courses.

Advantages of Linear Search

• Simplicity
• Efficient for small data sets
• Memory efficiency
• Flexibility

Disadvantages of Linear Search

• Time complexity
• Limited applicability
• Inefficient for multiple searches
• Space complexity

Working of Linear Search

• Every element is evaluated as a possible match for the key and tested for it.
• If an element matches the key, the search is successful, and the index of that element is returned.
• If no elements are found that match the key, the search returns "No match found".