Implementing hash table using Chaining through Doubly Linked List is similar to implementing Hashtable using Singly Linked List. The only difference is that every node of Linked List has the address of both, the next and the previous node. This will speed up the process of adding and removing elements from the list, hence the time complexity will be reduced drastically.
If we have a Singly linked list:
If we are at 3 and there is a need to remove it, then 2 need to be linked with 4 and as from 3, 2 can’t be accessed as it is singly linked list. So, the list has to be traversed again i.e O(n), but if we have doubly linked list i.e.1<->2<->3<->4
2 & 4 can be accessed from 3, hence in O(1), 3 can be removed.
Below is the implementation of the above approach:
Value 5 was successfully added at key 4 Element found at key 4: 5 Element was successfully removed at the key 4
- Find count of common nodes in two Doubly Linked Lists
- Sorted merge of two sorted doubly circular linked lists
- Construct a Maximum Sum Linked List out of two Sorted Linked Lists having some Common nodes
- Create a linked list from two linked lists by choosing max element at each position
- QuickSort on Doubly Linked List
- Reverse a Doubly Linked List | Set-2
- Reverse a Doubly Linked List
- Difference between Singly linked list and Doubly linked list
- XOR Linked List – A Memory Efficient Doubly Linked List | Set 2
- XOR Linked List - A Memory Efficient Doubly Linked List | Set 1
- Implementation of Deque using doubly linked list
- Rotate Doubly linked list by N nodes
- Merge Sort for Doubly Linked List
- Priority Queue using doubly linked list
- Sort the biotonic doubly linked list
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