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# Searching in Data Structure Different Search Methods Explained

Searching is an important operation in data structures. It involves looking for a specific element in a collection of elements and determining whether it is present or not. There are several methods for searching in data structures, including:

1. Linear search: This is the most basic search method. It involves going through the elements of a data structure one by one until the element being searched for is found or it is determined that the element is not present. This method is suitable for searching in unsorted lists or arrays.
2. Binary search: This method is used for searching in sorted lists or arrays. It involves dividing the list or array into two halves and comparing the element being searched for with the middle element. If the element is smaller, the search is continued in the first half of the list, otherwise it is continued in the second half. This method is faster than linear search as it reduces the number of comparisons required to find the element.
3. Hash search: This method is used for searching in hash tables. It involves using a hash function to map the element being searched for to a specific location in the hash table. This method is faster than linear search and binary search as it requires only one comparison to find the element.
4. Interpolation search: This method is similar to binary search, but it uses an interpolation formula to determine the position of the element being searched for in the list or array. This method is suitable for searching in large, uniformly distributed lists or arrays.
5. Depth-first search (DFS): This method is used for searching in tree and graph data structures. It involves starting at the root node and exploring as far as possible along each branch before backtracking.
6. Breadth-first search (BFS): This method is also used for searching in tree and graph data structures. It involves starting at the root node and exploring all of the neighbor nodes at the present depth before moving on to the nodes at the next depth level.