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Data Structures With JavaScript: Singly-Linked List and Doubly-Linked List

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This post is part of a series called Data Structures in JavaScript.
Data Structures With JavaScript: Stack and Queue
Data Structures With JavaScript: Tree
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What You'll Be Creating

Two of the most commonly taught data structures in computer science are the singly-linked list and doubly-linked list. 

When I was taught these data structures, I asked my peers for analogies to conceptualize them. What I heard were several examples, such as a list of groceries and a train. These analogies, as I eventually learned, were inaccurate. A grocery list was more analogous a queue; a train was more analogous to an array. 

As more time passed, I eventually discovered an analogy that accurately described a singly-linked list and a doubly-linked list: a scavenger hunt. If you're curious about the relationship between a scavenger hunt and a linked list, then read below for the answer!

A Singly-Linked List

In computer science, a singly-linked list is a data structure that holds a sequence of linked nodes. Each node, in turn, contains data and a pointer, which can point to another node.

Nodes of a singly-linked list are very similar to steps in a scavenger hunt. Each step contains a message (e.g. "You've reached France") and pointers to the next step (e.g. "Visit these latitude and longitude coordinates"). When we start sequencing these individual steps to form a sequence of steps, we are creating a scavenger hunt.  

Now that we have a conceptual model of a singly-linked list, let's explore the operations of a singly-linked list.

Operations of a Singly-Linked List

Since a singly-linked list contains nodes, which can be a separate constructor from a singly-linked list, we outline the operations of both constructors: Node and SinglyList.

Node

  • data stores a value.
  • next points to the next node in the list.

SinglyList

  • _length retrieves the number of nodes in a list.
  • head assigns a node as the head of a list.
  • add(value) adds a node to a list.
  • searchNodeAt(position) searches for a node at n-position in our list.
  • remove(position) removes a node from a list.

Implementation of a Singly-Linked List 

For our implementation, we will first define a constructor named Node and then a constructor named SinglyList

Each instance of Node needs the ability to store data and the ability to point to another node. To add this functionality, we will create two properties: data and next, respectively. 

Next, we need to define SinglyList:

Each instance of SinglyList will have two properties: _length and head. The former is assigned the number of nodes in a list; the latter points to the head of the list—the node at the front of the list. Since every new instance of SinglyList does not contain a node, the default value of head is null and the default value of _length is 0.

Methods of a Singly-Linked List

We need to define methods that can add, search, and remove a node from a list. Let's start with adding a node. 

1 of 3: add(value)

Awesome, let's now implement the functionality to add nodes to a list. 

Adding a node to our list involves many steps. Let us start from the beginning of our method. We use the argument of add(value) to create a new instance of a Node, which is assigned to a variable named node. We also declare a variable named currentNode and initialize it to the _head of our list. If there are no nodes in the list, then the value of head is null

After this point in our code, we handle two use cases. 

The first use case considers adding a node to an empty list. If head does not point to a node, then assign node as the head of our list, increment the length of our list by one, and return node

The second use case considers adding a node to a non-empty list. We enter the while loop, and during each iteration, we evaluate if currentNode.next points to another node. (During the first iteration, currentNode is always pointing to the head of a list.) 

If the answer is no, we assign node to currentNode.next and return node

If the answer is yes, we enter the body of the while loop. Inside the body, we reassign currentNode to currentNode.next. This process is repeated until currentNode.next no longer points to another node. In other words, currentNode points to the last node of our list.

The while loop breaks. Finally, we assign node to currentNode.next, we increment _length by one, and then we return node

2 of 3: searchNodeAt(position)

We can now add nodes to our list, but we cannot search for nodes at specific positions in our list. Let's add this functionality and create a method named searchNodeAt(position), which accepts an argument named position. The argument is expected to be an integer that indicates a node at n-position in our list.  

The if statement checks for the first use case: an invalid position is passed as an argument.

If the index passed to searchNodeAt(position) is valid, then we reach the second use case—the while loop. During each iteration of the while loop, currentNode—which first points to head—is reassigned to the next node in the list. This iteration continues until count is equal to position. 

When the loop finally breaks, currentNode is returned. 

3 of 3: remove(position)

The final method we will create is named remove(position)

Our implementation of remove(position) involves three use cases: 

  1. An invalid position is passed as an argument.
  2. A position of one (head of a list) is passed as an argument.
  3. An existent position (not the first position) is passed as an argument. 

The first and second use cases are the simplest to handle. In regards to the first scenario, if the list is empty or a non-existent position is passed, an error is thrown. 

The second use case handles the removal of the first node in the list, which is also head. If this is the case, then the following logic occurs:

  1. head is reassigned to currentNode.next.
  2. deletedNode points to currentNode
  3. currentNode is reassigned to null
  4. Decrement _length of our list by one.
  5. deletedNode is returned. 

The third scenario is the hardest to understand. The complexity stems from the necessity of tracking two nodes during each iteration of a while loop. During each iteration of our loop, we track both the node before the node to be deleted and the node to be deleted. When our loop eventually reaches the node at the position we want to remove, the loop terminates. 

At this point, we hold references to three nodes: beforeNodeToDeletenodeToDelete, and deletedNode. Prior to deleting nodeToDelete, we must assign its value of next to the next value of beforeNodeToDelete. If the purpose of this step seems unclear, remind yourself that we have a list of linked nodes; just removing a node breaks the link from the first node of the list to the last node of the list. 

Next, we assign deletedNode to nodeToDelete. Then we set the value of nodeToDelete to null, decrement the length of the list by one, and return deletedNode

Complete Implementation of a Singly-Linked List

The complete implementation of our list is here: 

From Singly to Doubly

Awesome, our implementation of a singly-linked list is complete. We can now use a data structure that adds, removes, and searches nodes in a list that occupy non-contiguous space in memory. 

However, at this moment, all of our operations begin from the beginning of a list and run to the end of a list. In other words, they are uni-directional. 

There may be instances where we want our operations to be bi-directional. If you considered this use case, then you have just described a doubly-linked list.

A Doubly-Linked List

A doubly-linked list takes all the functionality of a singly-linked list and extends it for bi-directional movement in a list. We can traverse, in other words, a linked list from the first node in the list to the last node in the list; and we can traverse from the last node in the list to the first node in the list. 

In this section, we will maintain our focus primarily on the differences between a doubly-linked list and a singly-linked list. 

Operations of a Doubly-Linked List 

Our list will include two constructors: Node and DoublyList. Let us outline their operations.

Node 

  • data stores a value.
  • next points to the next node in the list.
  • previous points to the previous node in the list.

DoublyList

  • _length retrieves the number of nodes in a list.
  • head assigns a node as the head of a list.
  • tail assigns a node as the tail of a list.
  • add(value) adds a node to a list.
  • searchNodeAt(position) searches for a node at n-position in our list.
  • remove(position) removes a node from a list.

Implementation of a Doubly-Linked List 

Let write some code! 

For our implementation, we will create a constructor named Node:

To create the bi-directional movement of a doubly-linked list, we need properties that point in both directions of a list. These properties have been named previous and next

Next, we need to implement a DoublyList and add three properties: _length, head, and tail. Unlike a singly-linked list, a doubly-linked list has a reference to both the beginning of a list and the end of a list. Since every instance of a DoublyList is instantiated without nodes, the default values of head and tail are set to null.

Methods of a Doubly-Linked List

We will now explore the following methods: add(value), remove(position), and searchNodeAt(position). All of these methods were used for a singly-linked list; however, they must be rewritten for bi-directional movement. 

1 of 3: add(value)

In this method, we have two scenarios. First, if a list is empty, then assign to its head and tail the node being added. Second, if the list contains nodes, then find the tail of the list and assign to tail.next the node being added; likewise, we need to configure the new tail for bi-directional movement. We need to set, in other words, tail.previous to the original tail. 

2 of 3: searchNodeAt(position)

The implementation of searchNodeAt(position) is identical to a singly-linked list. If you forgot how to implement it, I've included it below: 

3 of 3: remove(position)

This method will be the most challenging to understand. I'll display the code and then explain it. 

remove(position) handles four use cases: 

  1. The position being passed as an argument of remove(position) is non-existent. In this case, we throw an error. 
  2. The position being passed as an argument of remove(position) is the first node (head) of a list. If this is the case, we will assign deletedNode to head and then reassign head to the next node in the list. At this moment, we must consider if our list has more than one node. If the answer is no, head will be assigned to null and we will enter the if part of our if-else statement. In the body of if, we must also set tail to null—in other words, we return to the original state of an empty doubly-linked list. If we are removing the first node in a list and we have more than one node in our list, we enter the else section of our if-else statement. In this case, we must correctly set the previous property of head to null—there are no nodes before the head of a list.  
  3. The position being passed as an argument of remove(position) is the tail of a list. First, deletedNode is assigned to tail. Second, tail is reassigned to the node previous to the tail. Third, the new tail has no node after it and needs its value of next to be set to null
  4. A lot is happening here, so I will focus on the logic more than each line of the code. We break our while loop once currentNode is pointing to the node at the position being passed as an argument to remove(position). At this moment, we reassign the value of beforeNodeToDelete.next to the node after nodeToDelete and, conversely, we reassign the value of afterNodeToDelete.previous to the node before nodeToDelete. In other words, we remove pointers to the removed node and reassign them to the correct nodes. Next, we assign deletedNode to nodeToDelete. Finally, we assign nodeToDelete to null.   

Finally, we decrement the length of our list and return deletedNode

Complete Implementation of a Doubly-Linked List

Here's the entire implementation: 

Conclusion

We have covered a lot of information in this article. If any of it appears confusing, read it again, and experiment with the code. When it eventually makes sense to you, feel proud. You have just uncovered the mysteries of both a singly-linked list and a doubly-linked list. You can add these data structures to your coding tool-belt! 

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