When you first start learning about data storage, arrays are usually the go-to. But inserting one person at the front requires moving every single item in an array, which is exhausting for a computer. This is the exact problem DSA linked lists were built to solve. Instead of needing a single, giant block of memory, a linked list scatters its data across different locations.
What is a DSA Linked List?
At its simplest, a linked list is a chain of nodes. Each node contains two main parts:
- Data: The actual information you want to store (an integer, a string, etc.).
- Next: A pointer that stores the address of the next node in the sequence.
Because these nodes aren’t required to sit next to each other in memory, you can add or remove them without reorganising the entire structure. This makes DSA linked lists operations highly efficient for dynamic applications.
Common Types of Linked Lists
Depending on how you need to navigate your data, you will choose between different structures:
1. Singly Linked List
A singly linked list is the most basic form. Navigation is strictly one-way—from the “Head” (the first node) to the “Tail” (the last node). The tail always points to NULL, signalling the end of the list.
2. Doubly Linked List
A doubly linked list adds a second pointer to every node. Each node knows about the “Next” node and the “Previous” node. This allows you to traverse the list both forwards and backwards, which is handy for browser history or “undo” buttons, though it does use slightly more memory.
3. Circular Linked List
In this version, the tail doesn’t point to NULL. Instead, it loops back to the head. This creates a never-ending circle, often used in multiplayer games to rotate turns between players.
DSA Linked Lists Operations
To manage a list effectively, you need to master four primary operations:
- Insertion: Adding a node at the beginning, end, or middle. Adding at the head is a “constant time” operation, meaning it is extremelyfast regardless of the list’s size.
- Deletion: Removing a node by updating the pointers of its neighbours to bypass it.
- Display: Walking through the list from head to tail to print or process the data.
- Search: Checking each node one by one to find a specific value.
Also Check:
- DSA Full Form in Programming: Data Structures and Algorithms Explained
- Top 100 DSA Interview Questions
- DSA Counting Sort
- DSA Selection Sort
DSA Linked Lists in C++
In C++, we typically use classes or structures to define the node. Here is a basic look at how you might structure a singly linked list.
#include <iostream>
struct Node {
int data;
Node* next;
};
void printList(Node* n) {
while (n != NULL) {
std::cout << n->data << ” -> “;
n = n->next;
}
std::cout << “NULL” << std::endl;
}
int main() {
Node* head = new Node();
Node* second = new Node();
head->data = 10;
head->next = second;
second->data = 20;
second->next = NULL;
printList(head);
return 0;
}
This snippet of DSA linked lists in C++ shows how pointers connect independent memory blocks to create a logical sequence.
DSA Linked Lists Python
In Python, we don’t use manual pointers like C++. Instead, we use object references. Implementing DSA linked lists python style is often considered more readable for beginners.
class Node:
def __init__(self, data):
self.data = data
self.next = None
class LinkedList:
def __init__(self):
self.head = None
def display(self):
temp = self.head
while temp:
print(temp.data, end=” -> “)
temp = temp.next
print(“None”)
# Usage
llist = LinkedList()
llist.head = Node(1)
llist.head.next = Node(2)
llist.display()
Even without explicit pointers, DSA linked lists in Python code follow the same logic: nodes holding data and references to their neighbours.
DSA Linked Lists in C
If you are working with a linked list in C, you will be using malloc to allocate memory and pointers to bridge the nodes. It is the most “hands-on” way to learn because you are responsible for cleaning up the memory (using free) once you are done. This manual control is why C remains a favourite for teaching the core mechanics of memory management.
Linked Lists vs. Arrays: A Comparison
| Feature | Arrays | Linked Lists |
| Memory Allocation | Static / Contiguous | Dynamic / Non-contiguous |
| Insertion/Deletion | Slow (requires shifting) | Fast (only update pointers) |
| Access Time | Fast (Random access) | Slow (Sequential access) |
| Memory Usage | Fixed size | Grows as needed |
FAQs
Q1: What is the main disadvantage of a singly linked list?
The primary downside is that you can only move in one direction. If you need to access a previous node, you have to start all over from the head, which is why a doubly linked list is often preferred for complex tasks.
Q2: How much memory does a linked list use?
Each node in a linked list must store data and a pointer to the next node, so it uses more memory than an array for the same data.
Q3: When should I use DSA linked list instead of arrays?
Use them when you don't know your data's size or when your app needs frequent insertions and deletions at the start or middle.
Q4: Can a doubly linked list have a circular structure?
Yes, this is called a circular doubly linked list. The head's previous pointer points to the tail, and the tail's next pointer points to the head, allowing for infinite bi-directional traversal.
Q5: Is searching fast in DSA linked list?
Unfortunately, no. To find an element, you must start at the head and check each node one by one. This results in a time complexity of O(n), unlike arrays which allow for O(1) access if you know the index.