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Searching sorting algorithm

 DATA STRUCTURE

UNIT: - 7

Searching, Sorting and Complexity: -

 Searching

         Sequential Search

         Binary Search

Sorting

         Selection sort

         Bubble sort

         Quick sort

         Merge sort

 

Searching: -

1. Searching algorithms are designed to check for an element or retrieve an element from any data structure where it is stored.

2. Searching is the process of finding some particular element from the list.

3. The search is said to be successful or unsuccessful depending upon whether the element that is being searched is found or not.

4. In this algorithm if the element is found in the list then the process is called successful and the process returns the location of that element, otherwise the search is called unsuccessful.

5. Two popular searching methods that are widely used are: -

a. Sequential search

b. Binary search

 

Sequential Search: -

1. Sequential search is the simplest searching algorithm and also known as linear search.

2. This searching can be applied for both list of item sorted or unsorted.

3. The key which is to be searched is compared with each element of the list one by one.

4. If key is matched with the element then the search is terminated.

5. If the key is not matched with any element from the list then search is failed.

Time Complexity: -

1. The worst case performance of this algorithm is roughly proportional to n and represented as O(n).

2. The best case performance in which the first comparison returns a match it requires a single comparison and hence it is O(1).

3. The average case time depends on the probability that the key will found in the list. The average and worst case is proportional to n hence it is O(n).

Algorithm for sequential search: -

    Linear_search (Array A, value Y)

Step 1: -    for i = 1 to n; (n= number of element in array A)

Step 2: -    if A[i] = Y then go to step 4

Step 3: -    if i>n then go to step 5

Step 4: -    print element found and go to step 6

Step 5: -    print element not found

Step 6: -    Exit

Program Logic: -

        linear_Search(list, value)

             for each item in the list

                 if match item == value

                 return the item found

             end if

        end for

end function linear_search

 

Binary Search: -

1. Binary search tree technique is very fast and efficient.

2. Binary search algorithm applied only for sorted list of element.

3. In Binary search key is compared with the middle element of the given list, if key found search got stop.

4. Binary search followed divide and conquer approach in which the give item list is divide into two half after comparing middle element.

5. If key is not found then the key is searched in two halves depending upon the result produced through the match.

 

Time Complexity: -

1. The worst case performance of this algorithm is roughly proportional to lgn and represented as O(log n).

2. The best case performance in which the first comparison returns a match it requires a single comparison and hence it is O(1).

3. The average case time depends on the probability that the key will found in the list. The average and worst case is proportional to llgn hence it is O(log n).

 

Algorithm for sequential search: -

    Binary_search (Array A, value Y)

Step 1: -    Initialize i as first index and j as last index;

Step 2: -    while i <= j;

Step 3: -    (mid= (i+j)/2)

Step 4: -    if key == arr[mid] go to step 8

Step 5: -    else, compare key with mid is it greater then mid or smaller

Step 6: -    if mid < key, j= mid-1, go to step 2

Step 7: -    else, mid > key, i=mid + 1 go to step 2

Step 8: -    print element found go to step 10

Step 9: -    print element not found

Step 10: -  exit;

Program Logic: -

         binary_Search(arr, i, j, key)

             while(i<=j)

             mid = (i+j)/2;

if (key == arr[mid])

return k; //element found

if (key < arr [mid])

j = k-1;

else

i= k+1;

end while

return -1 //element not found

    end function binary_search

         

 

 Next update will available soon..!!

THANK YOU
Regards,

Diploma students

 

 

 

 

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