Queue Implementation Using Linked List in DSA Java - Time & Space Complexity

Time Complexity: Queue Implementation Using Linked List

O(1)

Understanding Time Complexity

We want to understand how fast the main actions of a queue using a linked list happen as the queue grows.

How does adding or removing items take more or less time when the queue gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

public class Queue {
    private Node front, rear;

    private static class Node {
        int data;
        Node next;
        Node(int d) { data = d; next = null; }
    }

    public void enqueue(int item) {
        Node newNode = new Node(item);
        if (rear == null) {
            front = rear = newNode;
            return;
        }
        rear.next = newNode;
        rear = newNode;
    }

    public int dequeue() {
        if (front == null) return -1;
        int value = front.data;
        front = front.next;
        if (front == null) rear = null;
        return value;
    }
}

This code adds items to the end and removes items from the front of a queue using a linked list.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Adding or removing one node at a time without loops.
• How many times: Each enqueue or dequeue runs once per call, no loops inside.

How Execution Grows With Input

Each add or remove action takes the same small steps no matter how many items are in the queue.

Input Size (n)	Approx. Operations
10	5-6 steps
100	5-6 steps
1000	5-6 steps

Pattern observation: The time to add or remove does not grow with the queue size; it stays constant.

Final Time Complexity

Time Complexity: O(1)

This means adding or removing an item takes the same short time no matter how big the queue is.

Common Mistake

[X] Wrong: "Removing an item takes longer as the queue grows because you have to move through all nodes."

[OK] Correct: The queue keeps track of the front node, so removing just changes a pointer without walking through the list.

Interview Connect

Knowing that queue operations are constant time shows you understand efficient data structure design, a key skill in many coding challenges.

Self-Check

"What if we used a singly linked list without a rear pointer? How would the time complexity of enqueue change?"

Practice

1. What is the main advantage of implementing a queue using a linked list over an array?

easy

A. Dynamic size, no fixed limit on queue length

B. Faster access to elements by index

C. Uses less memory than arrays

D. Simpler to implement than arrays

Solution

1. Step 1: Understand queue size limitation in arrays

   Arrays have fixed size, so queues implemented with arrays have a maximum capacity.

2. Step 2: Linked list allows dynamic size

   Linked lists can grow or shrink as needed, so queues using linked lists have no fixed size limit.

3. Final Answer:

   Dynamic size, no fixed limit on queue length -> Option A

4. Quick Check:

   Linked list queue size = dynamic [OK]

Hint: Linked list queues grow dynamically, arrays do not [OK]

Common Mistakes:

• Thinking arrays always use less memory
• Confusing access speed with size flexibility
• Assuming linked lists are simpler to implement

2. Which of the following is the correct way to declare a node class for a linked list queue in Java?

easy

A. class Node { int data; int next; }

B. class Node { int data; Node prev; }

C. class Node { Node data; Node next; }

D. class Node { int data; Node next; }

Solution

1. Step 1: Identify node fields for linked list queue

   A node should store data and a reference to the next node.

2. Step 2: Check each option's correctness

   class Node { int data; Node next; } has int data and Node next, which is correct. Others have incorrect types or missing next pointer.

3. Final Answer:

   class Node { int data; Node next; } -> Option D

4. Quick Check:

   Node stores data + next pointer [OK]

Hint: Node must link to next node, not previous or int [OK]

Common Mistakes:

• Using 'prev' pointer instead of 'next' for queue node
• Declaring next as int instead of Node
• Using Node type for data field

3. What will be the output after executing the following code snippet for a linked list queue?

Queue q = new Queue();
q.enqueue(10);
q.enqueue(20);
q.dequeue();
q.enqueue(30);
q.display();

Assuming display() prints elements front to rear separated by ' -> ' and ends with ' -> null'.

medium

A. 20 -> 30 -> null

B. 10 -> 20 -> 30 -> null

C. 30 -> null

D. 20 -> null

Solution

1. Step 1: Trace enqueue and dequeue operations

   Enqueue 10: queue = 10
   Enqueue 20: queue = 10 -> 20
   Dequeue: removes 10, queue = 20
   Enqueue 30: queue = 20 -> 30

2. Step 2: Display queue elements

   Queue elements front to rear are 20 followed by 30, so output is '20 -> 30 -> null'.

3. Final Answer:

   20 -> 30 -> null -> Option A

4. Quick Check:

   After dequeue, front is 20, then 30 [OK]

Hint: Dequeue removes front; enqueue adds rear [OK]

Common Mistakes:

• Not removing the first element on dequeue
• Appending new elements at front instead of rear
• Confusing order of elements in display

4. Identify the error in this dequeue method of a linked list queue:

public int dequeue() {
  if (front == null) {
    System.out.println("Queue is empty");
    return -1;
  }
  int value = front.data;
  front = front.next;
  if (front == null) {
    rear = null;
  }
  return value;
}

medium

A. Should update rear before front

B. No error, method works correctly

C. Returns wrong value after dequeue

D. Does not handle empty queue properly

Solution

1. Step 1: Check empty queue handling

   Method checks if front is null and returns -1 with message, which is correct.

2. Step 2: Check updating front and rear pointers

   After removing front node, front is updated to next node. If front becomes null, rear is also set to null. This is correct to keep queue consistent.

3. Final Answer:

   No error, method works correctly -> Option B

4. Quick Check:

   Dequeue updates front and rear properly [OK]

Hint: Set rear null only if front becomes null after dequeue [OK]

Common Mistakes:

• Not setting rear to null when queue becomes empty
• Returning wrong value after dequeue
• Not checking for empty queue before dequeue

5. You want to implement a method reverseQueue() that reverses the order of elements in a linked list queue without using extra data structures. Which approach is best?

hard

A. Create a new linked list and enqueue elements in reverse order

B. Traverse linked list and swap data of front and rear nodes repeatedly

C. Use recursion to dequeue elements and enqueue them back in reverse order

D. Use a stack to store elements and then enqueue back

Solution

1. Step 1: Understand constraints

   We cannot use extra data structures like stack or new linked list, so options C and D are invalid.

2. Step 2: Evaluate remaining options

   Traverse linked list and swap data of front and rear nodes repeatedly swaps data repeatedly but is inefficient and complex. Use recursion to dequeue elements and enqueue them back in reverse order uses recursion to dequeue all elements, then enqueue them back in reverse order, effectively reversing the queue without extra structures.

3. Final Answer:

   Use recursion to dequeue elements and enqueue them back in reverse order -> Option C

4. Quick Check:

   Recursion reverses queue without extra structures [OK]

Hint: Recursion can reverse queue without extra storage [OK]

Common Mistakes:

• Using extra data structures despite constraints
• Trying to swap node data instead of rearranging nodes
• Not handling empty or single-element queue cases