Searching Algorithms in Data Structures

Search algorithms are methods used to find a specific element or value in a data structure. These algorithms are used in various types of data structures, such as arrays, linked lists, sets, and maps. In this answer, we will discuss different types of search algorithms, their working principles, benefits, and examples.

Definition: A simple and direct search technique in which each element of a list is checked in order until the desired element is found.

How it works: Starts from the first element and compares each element with the desired one.

Time Complexity: O(n) in average and worst cases.

Definition: An efficient search technique that works on sorted data structures. It searches by dividing the list in half and using a pivot element.

How it works: Selects the middle element. If the pivot is smaller than the desired element, it searches in the upper half; if larger, it searches in the lower half.

Time Complexity: O(log n) in average and worst cases.

Definition: Another search technique that works on sorted data. It checks elements by jumping, then uses a linear search in the required block.

How it works: First, a jump length is determined (usually √n). Elements are checked by jumping until the location of the desired element is determined, then a linear search is performed.

Time Complexity: O(√n).

Definition: A search technique that works like binary search but is used to estimate the distribution of data.

How it works: First, the approximate location of the pivot is calculated based on the position of the desired value.

Time Complexity: O(log log n) in the average case.

Definition: Another search technique similar to binary search, but it uses the Fibonacci sequence for partitioning.

How it works: First, a Fibonacci number equal to the length of the list is calculated. Then it is used as a pivot, and the search is conducted in the same way as binary search.

Time Complexity: O(log n).