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
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Diploma students
Thank you sir
ReplyDeleteVery helpful notes sir
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