A. static and dynamic array implementation.
 B. Usin STL implementation.

 The problem with array is that it is not efficient in terms of memory. It always double the size, loss 
 of memory,but it is not in linked list but required double size, another to save addrress.
 Time comlexity of following operation in linked list:
   A. Insertion: O(N)
   B. Deletion:  O(N)
   C. Access:    O(N)

 It is LIFO (last in, first out).
 Uses of stack:
    A. Used to undo in text editor.
    B. Tower of annoy problem.
    C. To check brackets in code in text editor.
    D. Used in dfs.

Queue implementaion using single linked list. Queue is FIFO (first in, first out)
Time comlexity of following operation in queue:
   A. ENQUEUE: O(1)
   B. DEQUEUE:  O(1)
   C. SIZE:    O(N)

In periority queue, each element has some periority and according to which enqueue, dequeue and other 
function is implemented. Binary tree is used for implmentation. Hash table is used to remove element 
value wise in O(Log N).
  A. Enqueue: O(Log N)
  B. Dequeue: O(Log N)
  C. Size: O(1)
  D. Remove_using value: O(Log N)
  E. Dequeue using index: O(Log N)

 Union find is used to uinon two set and find is used to find in which set value belongs.
  A. union: aplha(n)
  B. Find: aplha(n)
  C. construct: O(n)

BST is tree which is acylic and has maximum two child for each parent. BST child has some constraint i.e. 
Left child is less than parent and right child is more than parent with respect to comparision function.
   A. Add element: O(Log N) 
   B. Remove element: O(Log N)
   C. Present: O(Log N)
 Travelsal in BST:
   A. Preorder (first left).
   B. Inorder.
   C. Postorder (first right).
   D. Level (level wise).

Hash table is key value pair, having hash function(H(x)) which which has input key and value, and output in 
specific range. Hash function map to only value in range which is index of our hash function. Key is called 
hasable means key used is immutable and key is in domain of hash function. Aplha is sensitivity feactor, 
which is used to remove over size. Their may be condition when different set of key value pair point to 
same index, such condtion is known as collision. Their are many collision resolution method, here we are
going to explore:
  A. Seperate chaining: Used extra linked list to save pair for each index.
  B. Open addresing: Used probing to change index if already value exist at that index.
    1. Linear probing: P(x) = a * x + b.
    2. Quadratic probing: P(x) = a * X^2 + b * x + c.
    3. Double hashing: P(x) = x * H2(k).
 For optimise probing their is condtion on probing function to avoid cylce aslo after using probing:
  A. Linear probing: GCD( A,N) should be one and a = 1 is used many time, if a!=1 than as capacitity 
     is increased, according to which a should change.
  B. Quadratic probing: 
    1. P(X) = X^2 and n (size of table) as prime>3 and alpha <=0.5.
    2. P(x) = (X^2 +X)/2 and N is in poer of two (Using here).
    3. P(x) = ((-1)^X) * X^2.
  C. Double hashing: To avoid cycle, delta is defined as H2(k) % N. If delta is zero hange it zero, else
  unchanged. And final delta is returned, where N is prime.