This is the 3rd entry in the “Practical Computer Science in Ruby” series! Today we are going to talk about linked list.
So what’s a linked list?
Like the name says, a linked list is a way to store data in a list format (thanks, Captain Obvious!).
The “linked” part comes from the fact that data is stored in a node & these nodes are linked to each other in a sequential manner.
How is this different from an array?
Linked List vs Array
A linked list has different performance characteristics than an array. That’s one reason why you may want to pick one over the other.
This means that a linked list can be more efficient for certain tasks than an array.
In a linked list there is no indexing, no random access, meaning that you can’t reach out for an item in the middle of the list.
You have to start at the “head” of the list & follow the links until you find the node you want or until the end of the list.
Removing (or adding) an item from the middle of a linked list is a lot faster.
All you have to do is change the “next” pointer for one node.
But if you want to delete an element from the middle of an array you will leave a gap & to close that gap you have to move all the elements on the right of the deleted element.
Not very efficient if you have to do this often!
If we want to insert in the middle of an array we have to move all the array elements to create an empty space.
Let’s see a code example:

a = [1,2,3,4,5,6,7,8] def insert(arr, item, pos) tmp = arr[pos] arr[pos] = item arr.replace(arr[0..pos] + [tmp] + arr[pos+1..1]) end insert(a, 99, 3) p a 
Note: There is also a builtin Array#insert method, but I wanted to show you how this method works.
What is the performance impact of inserting an item in the middle of a list?
Here’s a benchmark:

Comparison: LinkedList: 1815407.9 i/s Array: 18090.3 i/s  100.35x slower 
Big difference here, but it also depends a lot on the size of the LinkedList
since we have to search for the node.
Another way to compare two data structures is to look at a time complexity table (this assumes you don’t have to search a node for insertion & deletion):
Data Structure 
Access 
Search 
Insertion 
Deletion 
Array 
O(1) 
O(n) 
O(n) 
O(n) 
Linked List 
O(n) 
O(n) 
O(1) 
O(1) 
Looking for realworld applications?
Here’s a pull request by Aaron Patterson where he speeds up Ruby Gems by using a linked list:
https://github.com/rubygems/rubygems/pull/1188
Linked List Implementation
Ruby doesn’t include a LinkedList
class so we need to create our own.
We want the following operations to be available:
 append (to the end of the list)
 append_after
 delete
 find
Here’s one possible implementation:
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class LinkedList def initialize @head = nil end def append(value) if @head find_tail.next = Node.new(value) else @head = Node.new(value) end end def find_tail node = @head return node if !node.next return node if !node.next while (node = node.next) end def append_after(target, value) node = find(target) return unless node old_next = node.next node.next = Node.new(value) node.next.next = old_next end def find(value) node = @head return false if !node.next return node if node.value == value while (node = node.next) return node if node.value == value end end def delete(value) if @head.value == value @head = @head.next return end node = find_before(value) node.next = node.next.next end def find_before(value) node = @head return false if !node.next return node if node.next.value == value while (node = node.next) return node if node.next && node.next.value == value end end def print node = @head puts node while (node = node.next) puts node end end end 
This particular implementation doesn’t keep track of the tail, it finds the tail when appending a new item. This makes the append operation linear time (O(n)
). In the video below I show you another implementation where I append the elements at the front.
And here is our node class:

class Node attr_accessor :next attr_reader :value def initialize(value) @value = value @next = nil end def to_s "Node with value: #{@value}" end end 
We can use it like this:

list = LinkedList.new list.append(10) list.append(20) list.append(30) list.append_after(10, 15) list.append_after(20, 25) list.print 
This is a basic “SinglyLinked List” implementation.
You also have other types of linked list:
 DoublyLinked List
 Circular Linked List
In the doublylinked list every node has two pointers: one to the next node & another to the previous node.
This allows for more flexibility when searching the list, but also requires extra work when making changes to the list.
A circular linked list is the same than a doublylinked list, but the last node is connected to the head node.
Video
Summary
You have learned about linked lists, a data structure which you could consider if you are doing a lot of adding & removing of elements in the middle of an array.
It could also come up in a coding interview, so it’s worth learning even if it’s just for that.
Don’t forget to share this post using the buttons below so more people can benefit from this knowledge ðŸ™‚
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