Sequential
Search
slides
Searching
• Searching :
– Information retrieval is one of the most
important application of computers.
– EG: Looking for a Name by giving the
telephone number.
– We give one piece of information (KEY)
and we are asked to find a record that
contains other information associated
with the key
Searching
• Searching for the keys that locate records is the
most time consuming action in a program
• Two Types of Searching are there,
1) external searching
Searching in external storage devices
(Disk,Tapes etc..)
2) internal searching
Searching within the computer memory
Searching
• Sequential Search :
– Start at the first piece of data and look
at it and if it no then keep going until
you find what you are looking for or
until you have reached the last.
– EG :
– Analysis :
– When to Use?
Sequential search
• Find the marks of the students from the
Data structures and algorithms course
using an array. ( Key - ID)
array name is ‘ a ‘
// create
A
R
R
A
Y
ID 456
60
80
For ( I =0; I < size; I++)
{ if a[I].id == ‘123’
cout << a[I].id<<a[I].mark1;
found = true }
if (found !=true) cout << “Not
in the List”
Sequential Search
Algorithm2:
cin >>target;
found = 0;
I =0;
while(I<n) &&(found==0)
if (array[I]==target)
found =1;
Prev Alg: Depends on n
But this one depends not
only on n but also the
position of the target
Sequential Search
• Two Kinds of result
1) Successful
2) UnSuccessful
Best Case - 1st element
O(1)
(456)
Worst Case - nth element
O(n)
(last)
Sequential search
1)It is useful for limited sized data sets as it is
simple and does not require data to be structured
in any way
2)when the data to be searched is constantly
changing
Dis : time consuming (large list)
Any there other suitable data structures?
This algorithm is well suited for implementation
with linked list - follow ‘next’ pointer until we find
or until we have reached the last
adv: addition/deletion is easy
Binary Search
• How it works?
• Binary - two . List is broken down to two parts
and searched
• working : Compare the target with the one in the
center of the list and then restrict our attention
to only the first or second half depending on
whether the target comes before or after the
central one. ( we reduce the length to be
searched by half)
Binary Search
• Rule - numbers must be in sorted
order
• Steps : 1. L = Low ( first index)
2. H = High (last index)
3. M = Mid ( ( l + h )/ 2 )
• 1. mark l & h
• 2. Find Mid
Binary search
3. Check whether mid = x if so return
index
4. If not , check whether x is > then
bring low to mid +1 and carry on the
same process
5. If < then bring high to mid-1 and
carry on the same process
6. Until you find the value or if low and
high cross each other
Binary search
EG : 10 20 30 40 50 60 70
Find X = 20 (search value)
10 20 30 40 50 60 70
low
high
1. Mid = l+h/2 = 1+7/2 = 4
10 20 30 40 50 60 70
low
h Mid
high = mid -1
Binary search
10 20 30 40 50 60 70
low
h
mid = l +h/2 = 1+3/2 =2
10 20 30 40 50 60 70
l m h
check x = a[mid] , yes matching so
return index - ie 2