Linked Lists

Let's learn about Doubly Linked Lists!


Elements probably not laid out sequentially in memory Access a subscript/index via traversing nodes (which is slow) Implemented as a “linked list”

Linked List

Internally has “nodes”.

Using this example:

char* data = "hello"

(Where data[0] == h and data[4] == o)

In this case, we have a char and two pointers in each node:

  1. char data would be 'h'
  2. Node *next would be a pointer to the next node ('e')

Doubly Linked List

Each list element (ie node) contains a pointer to the next node in the list. Along with the data each node holds.

Here’s a basic visual for a linked list!

Class LinkedList is an archetypal doubly linked list. Where Node structures and internal list details are kept private. Also, note that all member functions are defined inside the class declaration. (No separate .h and .cpp/.cc files.) Template classes are usually defined this way. For this class, the param T is the type of the list elements. You can think of it as a dynamic or generic way to hold data!

Starter Code

For this course, we will be building off of this code! If you would like to follow along with the code, I recommend copying this template class.

template<typename T>
class LinkedList {
  // A forward declaration for a nested type named "Node"
  // We can refer to the Node type in the body of public member functions even though it hasn't been fully defined yet
  struct Node;
  // Constructors
  // Destructors
  // other public member functions
  struct Node {
    T data;
    Node* next = nullptr;
    Node* prev = nullptr;
    // default constructor!
    Node(T value) : data(value), next(nullptr), prev(nullptr) {}
  Node* head = nullptr;
  Node* tail = nullptr;
  std::size_t list_size = 0;

A list type should almost always be a template type

An example of this is with vectors. std::vector is actually std::vector<T> (ie T is the element type)


1. No direct access (unlike an array)

Address of value at index 5 in an array: (ie a single integer addition).

array_variable + 5

Address of node representing index 5 in a linked list: (ie multiple pointer dereferences)


2. Overhead

Occupies more space than an array (overhead). An array of chars of size 3 holds 3 bytes. A doubly linked list of chars, size 3 holds up to 67 bytes (8 pointers, 3 chars) (more likely 88 bytes - memory alignment on 8-byte boundaries faster for CPU)

3. No Spacial Locality

(nodes likely not next to each other in memory) It may be difficult for the CPU cache to optimize.


1. Linked Lists Are Dynamic

Linked lists allow for efficient memory allocation as nodes can be dynamically allocated and deallocated, enabling flexible memory management compared to arrays, which have a fixed size. Linked lists can be constructed on the fly, accommodating elements as needed, making them suitable for situations where the size of the data is unknown in advance.

Linked lists can grow or shrink dynamically during runtime, allowing for efficient insertion and deletion of elements anywhere in the list without requiring resizing or shifting of elements, as is the case with arrays.

2. Efficiency:

Insertion and deletion operations at the beginning or end of a linked list (when you have direct access to the head or tail) can be performed in constant time O(1), regardless of the list size. This makes linked lists efficient for dynamic data structures. More on time complexity here.

Insertions and deletions in the middle of a linked list can also be efficient if you have direct access to the node where the operation is performed. Unlike arrays, linked lists don’t require shifting elements, resulting in faster operations.

Linked lists consume memory only for the actual data and the pointers connecting the nodes, making them memory-efficient compared to arrays, which may have unused space due to fixed-size allocation.

3. Versatility

Linked lists come in different forms, such as singly linked lists, doubly linked lists, and circular linked lists. Each variant offers unique advantages, allowing developers to choose the type that best fits their requirements.

4. Ease of Implementation

Linked lists are relatively easy to implement and understand compared to more complex data structures like trees and graphs. This simplicity makes them an excellent choice for learning data structures and algorithms.

If you want to access the source code for the completed list, I have it posted for public access here