Introduction
Searching
Algorithms
The searching algorithms
are used to search or find one or more than one element from a dataset. These
type of algorithms are used to find elements from a specific data structures.
Searching may be
sequential or not. If the data in the dataset are random, then we need to use
sequential searching. Search algorithms are designed to retrieve something
or retrieve an object from any data structure in which it is stored. Depending on
the type of search function, these algorithms are usually divided into two
categories:-
Sequential
Search: In this case, the list of elements are traverse by sequence to find
a value and if the desire value is present, it will show.
Interval Search:
These algorithm are used for searching in sorted data structures. This type of
search algorithms works much better than Linear Search as they often point to
the center of the search structure and divide the search space in half.
1. Linear
search:-
Linear search is
the easiest way to search. In this type of search, you have to traverse
sequentially. Every element is checked and when a match is found the item is
returned, otherwise the search continues until the end of data collection.
Linear search
algorithm where A is array and X is the value:-
Step 1: Set i to 1.
Step 2: if i > n then
go to step 7.
Step 3: if A[i] = x then
go to step 6.
Step 4: Set i to i + 1.
Step 5: Go to Step 2.
Step 6: Print Element x
Found at index i and go to step 8.
Step 7: Print element
not found.
Step 8: Exit
Example:
Linear search is the most
common searching algorithm. Its biggest advantage is that it’s ready-to-use —
it just always works, no extra prerequisites. It comes with a cost of time
though.
Linear search doesn’t care
if the collection is sorted or not, it just goes one-by-one element and checks
if it matches our key (key is an element I’m looking for). The worst case
scenario for this algorithm to find a key is O(n) where n is a number of elements.
It will happen in two cases:
1. Key element is the last one
2. Key element is not present


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