Queue Implementation Using Linked List in DSA Java - Execution Trace

Concept Flow - Queue Implementation Using Linked List

Create new node

↓

Is queue empty?

Yes→Set front and rear to new node

|No↓

Link rear.next to new node

↓

Update rear to new node

↓

Done

↓

For Dequeue

↓

Is queue empty?

Yes→Return empty message

|No↓

Save front node data

↓

Move front to front.next

↓

If front is null, set rear to null

↓

Return saved data

This flow shows how nodes are added at the rear and removed from the front in a linked list queue.

Execution Sample

DSA Java

enqueue(10)
enqueue(20)
dequeue()
enqueue(30)
dequeue()

This code adds 10 and 20 to the queue, removes one element, adds 30, then removes another element.

Execution Table

Step	Operation	Nodes in List	Pointer Changes	Visual State
1	enqueue(10)	10	front -> 10, rear -> 10	10 -> null
2	enqueue(20)	10 -> 20	rear.next -> 20, rear -> 20	10 -> 20 -> null
3	dequeue()	20	front -> 20	20 -> null
4	enqueue(30)	20 -> 30	rear.next -> 30, rear -> 30	20 -> 30 -> null
5	dequeue()	30	front -> 30	30 -> null
6	dequeue()	empty	front -> null, rear -> null	null

💡 Queue is empty after last dequeue, front and rear pointers set to null.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	After Step 6
front	null	Node(10)	Node(10)	Node(20)	Node(20)	Node(30)	null
rear	null	Node(10)	Node(20)	Node(20)	Node(30)	Node(30)	null
size	0	1	2	1	2	1	0

Key Moments - 3 Insights

Why do we update rear.next when enqueueing a new node?

Because rear.next must point to the new node to link it at the end, as shown in step 2 and 4 in the execution table.

What happens when we dequeue the last element?

Both front and rear pointers are set to null to indicate the queue is empty, as seen in step 6.

Why do we only move front pointer during dequeue?

Because dequeue removes from the front, so front moves to front.next; rear stays unless queue becomes empty (step 3 and 5).

Visual Quiz - 3 Questions

Look at the execution table, what is the visual state after step 2?

A 10 -> 20 -> null

B 20 -> 10 -> null

C 10 -> null

D 20 -> null

💡 Hint

Check the 'Visual State' column for step 2 in the execution table.

At which step does the queue become empty?

A Step 3

B Step 5

C Step 6

D Step 4

💡 Hint

Look for when 'Nodes in List' is 'empty' and pointers are null in the execution table.

If we enqueue(40) after step 6, what will be the front pointer?

A null

B Node(40)

C Node(30)

D Node(10)

💡 Hint

After queue is empty, enqueue sets front and rear to the new node (see concept flow).

Concept Snapshot

Queue using linked list:
- Enqueue adds node at rear
- Dequeue removes node from front
- If empty, front and rear are null
- rear.next links new node
- front moves on dequeue
- Size tracks number of nodes

Full Transcript

This visual trace shows how a queue is implemented using a linked list. Enqueue adds a new node at the rear, updating rear.next and rear pointer. Dequeue removes the front node by moving the front pointer forward. When the queue becomes empty, both front and rear pointers are set to null. The execution table tracks each step with the nodes in the list, pointer changes, and the visual linked list state. Variable tracker shows how front, rear, and size change after each operation. Key moments clarify why rear.next is updated on enqueue, why both pointers reset on empty, and why only front moves on dequeue. The quiz tests understanding of the visual states and pointer positions after operations.

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