It gives the idea of the asymptotic upper bound of execution time required for the algorithm with respect to a given condition. The notation used in search algorithms is O( n), where n is the number of comparisons done. The efficiency of a search algorithm is measured by the number of times a comparison of the search key is done in the worst case. There are other search algorithms such as the depth-first search algorithm, breadth-first algorithm, etc. Binary search method is considered as the best searching algorithms. Linear search is rarely practical because other search algorithms and schemes, such as the binary search algorithm and hash tables, allow significantly faster searching for all but short lists.įlow chart representation of Linear SearchĪ linear search algorithm is considered the most basic of all search algorithms. If each element is equally likely to be searched, then linear search has an average case of n+1/2 comparisons, but the average case can be affected if the search probabilities for each element vary. This type of searching algorithms sequentially checks each element of the list until a match is found or the whole list has been searched.Ī linear search runs in at worst linear time and makes at most n comparisons, where n is the length of the list. Let us understand each one of these types of searching algorithms in details with examples & illustrations-Ī linear search or sequential search is a method for finding an element within a list. There are few more types of algorithms left to be discussed here, but all cannot be covered in one post, so we will cover those left outs in another topic. Sublist Search (Search a linked list in another list).These type of searching algorithms are more efficient than Linear Search method, as they repeatedly target the center of the search structure and divide the search space in 2 half. Interval Search: These algorithms are specifically designed for searching in sorted data-structures.
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