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This presentation will you understand all about hashing and also different techniques used in it for encryption process
Hashing notes data structures (HASHING AND HASH FUNCTIONS)Kuntal Bhowmick
A Hash table is a data structure used for storing and retrieving data very quickly. Insertion of data in the hash table is based on the key value. Hence every entry in the hash table is associated with some key.
HASHING AND HASH FUNCTIONS, HASH TABLE REPRESENTATION, HASH FUNCTION, TYPES OF HASH FUNCTIONS, COLLISION, COLLISION RESOLUTION, CHAINING, OPEN ADDRESSING – LINEAR PROBING, QUADRATIC PROBING, DOUBLE HASHING
hashing is encryption process mostly used in programming language for security purpose.
This presentation will you understand all about hashing and also different techniques used in it for encryption process
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The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
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Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
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Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
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http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
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4. Introduciton
A hash function is any function
is that can be used to map data
of arbitrary size to a data of
fixed size. The values returned
by them are called hash values.
4
5. History
◦ The idea of hashing arose independently in different places.
◦ In January 1953, Hans Peter Luhn wrote an internal IBM memorandum
that used hashing with chaining.
◦ Open addressing with linear probing (relatively prime stepping) is
credited to Gene Amdahl, but Ershov (in Russia) had the same idea.
5
7. First we shall look at hashing.
• Hashing is used to reduce the
search time for an element in an
array or group of data.
• For this purpose, we map the
elements into the indices of the
array as same as their hash key.
7
8. First we shall look at hashing.
In this way, we actually can find an element directly
i.e. at O(1) constant time. And this is done by
mapping, which is the credit of hash functions.
We call each element a key and denote the array
as hash table.
8
9. HASH FUNCTION
Must return a valid table location
Easy to implement.
Should be 1-to 1 mapping (avoid collision).
If key1!=key2 then hash (key1)!=hash(key2)
9
10. HASH FUNCTION
A collision occurs when two distinct keys hash to the
same location in the array.
Should distributed the keys evenly.
Any key value k is equally likely to hash to any of the
m array locations.
10
11. STANDARD HASH FUNCTION
Hash value =key(mod) tablesize
Example:
4112041: 12041 mod 1000 = 41
4163490: 63490 mod 1000= 490
Tablesize should be a prime number for even
distribution
11
15. SEPARATE CHAINING
Usually implemented using linked lists.
To store an element in the hash table you
must insert it into a specific linked list. If there
is any collision (i.e. two different elements have
same hash value) then store both the elements
in the same linked list.
15
16. Let us consider a simple hash
function as “key mod 7” and
sequence of keys as 50, 700, 76,
85, 92, 73, 101.Then,
• 50 mod 7=1
• 700 mod 7=0
• 85mod 7=1
• 92 mod 7=1
• 73mod 7=3
• 101 mod 7=3
16
17. LINEAR PROBING
If a collision occurs, try the next cell sequently
F(i)=i
hi (x)=(hash(x) + i) mod TableSize,
Try hash(x) mod TableSize,(hash(x) + 1) mod
TableSize, (hash(x) + 2) mod
TableSize,(hash(x) +3) mod
TableSize,…………
17
18. Let us consider a simple
hash function as “key
mod 7” and sequence of
keys as 76, 93, 40, 47,
10, 73, 10,55
Here, (5+1) mod 7=6
(5+2) mod 7=0
18
19. QUADRATIC PROBING
Eliminate primary clustering
F(i)=i2
hi (x)=(hash(x) + i2) mod TableSize,
Try hash(x) mod TableSize,(hash(x) + 12) mod
TableSize, (hash(x) + 22) mod TableSize,(hash(x)
+32) mod TableSize,…………
The table must be at most half full and tablesize
must be prime, otherwisw insertion may fail(always
have a collision)
19
21. INSERT ALGORITHM
Hash-insert(T,k) // T= array that represent hash table
i = 0 to m // m = number of indices ,i=look counter
Repeat
• j = h(k,i) //J=hash value
• if T[j] == NIL
• T[j] = k
• return j
• else i = i + 1
until i == m
error “hash table overflow”
21
22. SEARCH ALGORITHM
Hash-Search(T,k)
i = 0
repeat
• j = h(k,i)
• If T[j] == k
• Return T[ j]
• i = i + 1
until T[j]== NIL or i == m
return NIL
22
24. while(ary[pos=! size) { // INT_MAX indicates that cell is empty. So if cell is empty loop will
break and goto bottom of the loop to insert element
if(ary[pos]== INT_MAX)
break;
pos = (pos+1)%hFn;
n++;
if(n==size)
break;
}
if(n==size)
printf("Hash table was full of elementsnNo Place to insert this elementnn");
else
ary[pos] = element; //Inserting element
}
24
25. • void search(int ary[],int hFn,int size){
• int element,pos,n=0;
•
• printf("Enter element you want to searchn");
• scanf("%d",&element);
•
• pos = element%hFn;
•
• while(n++ != size){
• if(ary[pos]==element){
• printf("Element found at index %dn",pos);
• break;
• }
25
26. • else
• if(ary[pos]==INT_MAX ||ary[pos]!=INT_MIN)
• pos = (pos+1) %hFn;
• }
• if(--n==size) printf("Element not found in hash tablen");
• }
• void display(int ary[],int size){
• int i;
•
• printf("IndextValuen");
•
•
26
27. • for(i=0;i<size;i++)
• printf("%dt%dn",i,ary[i]);
• }
• int main(){
• int size,hFn,i,choice;
•
• printf("Enter size of hash tablen");
• scanf("%d",&size);
•
• int ary[size];
•
• printf("Enter hash function [if mod 10 enter 10]n");
• scanf("%d",&hFn);
27
31. COMPLEXITY ANALYSIS
Since we have to search for keys at
indexes not same as the key, the
search time is not O(1). But it is still
much better than O(logn).
31
33. • Hoping that you have no question to us, we conclude our presentation. Yet if
someone wishes to embarrass us, other than our honorable teacher , I shall not
bother to answer my dear mates.