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In the computer field, we can't do without algorithms and data structures, but in data structures, we often need some clever structures to deal with some complicated data. Linked list is such a data structure that can help us solve this problem.

It can assist in forming other data structures such as queues.

Follow-up dynamic data structures such as binary search tree, balanced binary tree and red-black tree can be studied deeply on the basis of understanding linked lists.

If you are a computer beginner, learning about linked lists can help you understand recursion, because recursion needs to be understood in depth in subsequent binary trees.

Definition of linked list

In the algorithm (4th Edition), the linked list is defined as follows:

A linked list is a recursive data structure that is either null or a reference to a node (node) that also has an element and a reference to another linked list.

The data of the linked list is stored in the "Node":

Resize this operation, and by looking at the data structure of the linked list, we can find that:

The next of the last node points to NULL, and this node is the last node

Unlike arrays, which have to new a piece of space at once, there is no need to consider that the space is insufficient or wasted.

How much data is needed, how many nodes can be generated and connected.

In other words, linked lists have dynamic capabilities and do not need to deal with fixed capacity problems.

Because the linked list has this dynamic capability, it also lacks the ability of efficient random access (random access). Like an array, it cannot directly get the corresponding element through an index (index).

Because in the underlying mechanism, the space opened up by the array is continuously distributed in memory, we can directly find the corresponding offset of the index, directly calculate the memory address of the data storage, and take it out directly with O (1) complexity.

The linked list is connected by next, and each node has a different storage address, so we can only find the elements we are looking for through next.

Realization of linked list

These are the member variables and common methods of the linked list.

Add element operation of linked list

For data structures such as linked lists, it is convenient to add elements to the head or tail of the chain.

It is also easy to insert elements in the middle of the linked list, but pay attention to the order in which they are inserted

Node insertNode = new Node (e); insertNode.next = prevNode.next; prevNode.next = insertNode

After comparing the two sets of animations, you will soon wonder: can you use the same code to handle the insertion of the head and the middle of the linked list?

The answer is yes! You only need to introduce the concept of a virtual header node.

Then you can get the code to add elements to the linked list:

Delete element operation of linked list

For the delete element operation of the linked list, you need to find the precursor node of the target node.

Find element operation for prev.next = delNode.nextdelNode.next = null linked list

The location index of the virtual node can be regarded as-1

Modification element operation of linked list

The operation of finding elements based on the above linked list is easy to write out the modified element operations of the linked list.

Time complexity of linked list API description add (index, e) insert operation O (n) remove (index, e) delete operation O (n) set (index, e) modify operation O (n) get (index, e) search operation O (n) contains (index, e) is also a search operation O (n)

Because linked lists do not have indexes, linked lists lose the ability to access them as quickly as arrays, which makes the additions, deletions and queries of linked lists all O (n) level.

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