Dequeue Using Linked List in DSA Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a Dequeue (Double-Ended Queue)?

A Dequeue is a data structure where elements can be added or removed from both the front and the rear ends.

beginner

Why use a linked list to implement a Dequeue?

A linked list allows efficient insertion and deletion at both ends without shifting elements, making it ideal for Dequeue operations.

beginner

What are the main operations of a Dequeue using a linked list?

The main operations are: insert_front, insert_rear, delete_front, delete_rear, and display.

intermediate

How does delete_rear operation work in a linked list based Dequeue?

It removes the last node by traversing to the second last node and updating its next pointer to None, then freeing the last node.

intermediate

What is the time complexity of insert_front and delete_front in a linked list Dequeue?

Both insert_front and delete_front operations take O(1) time because they directly add or remove the first node.

Which operation is NOT supported by a Dequeue?

A Insert in the middle

B Delete from rear

C Delete from front

D Insert at front

Dequeue supports insertion and deletion only at the front and rear ends, not in the middle.

What is the advantage of using a linked list for Dequeue over an array?

A Uses less memory always

B Faster random access

C Fixed size

D Dynamic size and no shifting needed

Linked lists allow dynamic size and efficient insertions/deletions at both ends without shifting elements.

What happens when you delete the rear element in a singly linked list Dequeue?

A You must traverse to the second last node first

B You can directly remove the last node

C You remove the first node

D You cannot delete rear in singly linked list

To delete the rear node, you must find the second last node to update its next pointer to None.

What is the time complexity of deleting the rear node in a singly linked list Dequeue?

A O(1)

B O(n)

C O(log n)

D O(n log n)

Deleting the rear node requires traversal to the second last node, which takes O(n) time.

Which pointer is updated when inserting a node at the front of a linked list Dequeue?

A Rear pointer

B Next pointer of last node

C Next pointer of new node

D Previous pointer of new node

The new node's next pointer is set to the current front node, then front pointer is updated to new node.

Explain how insertion at the rear end works in a linked list based Dequeue.

Think about how to add a node at the end of a linked list.

Describe the steps to delete the front element from a linked list Dequeue.

Focus on removing the first node safely.

Practice

1. What is a dequeue (double-ended queue) implemented using a linked list?

easy

A. A queue where elements can only be added at the rear

B. A list that only allows insertion at the front

C. A stack implemented using arrays

D. A data structure where elements can be added or removed from both ends

Solution

1. Step 1: Understand dequeue operations

   A dequeue allows insertion and deletion from both front and rear ends.

2. Step 2: Linked list implementation

   Using a linked list, nodes can be added or removed from both ends efficiently.

3. Final Answer:

   A data structure where elements can be added or removed from both ends -> Option D

4. Quick Check:

   Dequeue = double-ended queue [OK]

Hint: Dequeue means double-ended queue, both ends allowed [OK]

Common Mistakes:

• Confusing dequeue with stack or simple queue
• Thinking insertion is only at one end
• Assuming array implementation only

2. Which of the following is the correct way to initialize an empty dequeue using a linked list in Python?

easy

A. class Dequeue: def __init__(self): self.front = None; self.rear = None

B. class Dequeue: def __init__(self): self.list = []

C. class Dequeue: def __init__(self): self.head = 0; self.tail = 0

D. class Dequeue: def __init__(self): self.front = 0; self.rear = 0

Solution

1. Step 1: Identify linked list pointers

   For linked list, front and rear pointers are initialized to None to indicate empty.

2. Step 2: Check options

   class Dequeue: def __init__(self): self.front = None; self.rear = None correctly initializes front and rear as None; others use incorrect types or structures.

3. Final Answer:

   class Dequeue: def __init__(self): self.front = None; self.rear = None -> Option A

4. Quick Check:

   Linked list empty pointers = None [OK]

Hint: Empty linked list pointers are None, not zero or list [OK]

Common Mistakes:

• Using list instead of linked list
• Initializing pointers with 0 instead of None
• Confusing front/rear with indices

3. What will be the output after performing these operations on an empty dequeue implemented with linked list?
dq.insert_rear(10)
dq.insert_front(20)
dq.insert_rear(30)
dq.delete_front()
Print the dequeue from front to rear.

medium

A. 20 -> 10 -> 30 -> null

B. 20 -> 30 -> null

C. 10 -> 30 -> null

D. 30 -> 10 -> 20 -> null

Solution

1. Step 1: Perform insert_rear(10) on empty dequeue

   Dequeue becomes: 10 -> null

2. Step 2: Perform insert_front(20)

   Dequeue becomes: 20 -> 10 -> null

3. Step 3: Perform insert_rear(30)

   Dequeue becomes: 20 -> 10 -> 30 -> null

4. Step 4: Perform delete_front()

   Remove 20 from front, dequeue becomes: 10 -> 30 -> null

5. Final Answer:

   10 -> 30 -> null -> Option C

6. Quick Check:

   After operations, front to rear = 10, 30 [OK]

Hint: Track each operation stepwise front to rear [OK]

Common Mistakes:

• Forgetting delete_front removes front element
• Mixing order of insert_front and insert_rear
• Printing rear to front instead of front to rear

4. Identify the error in this dequeue linked list method for deleting from rear:

def delete_rear(self):
    if self.rear is None:
        return None
    temp = self.rear
    self.rear = self.rear.next
    return temp.data

medium

A. Does not check if dequeue is empty

B. Incorrectly moves rear pointer forward instead of backward

C. Returns data before deleting node

D. Uses wrong variable name for rear

Solution

1. Step 1: Understand rear pointer movement

   In linked list, rear points to last node; to delete rear, rear must move backward (to previous node).

2. Step 2: Analyze code

   Code moves rear to rear.next (forward), which is incorrect for rear deletion.

3. Final Answer:

   Incorrectly moves rear pointer forward instead of backward -> Option B

4. Quick Check:

   Rear deletion moves pointer backward [OK]

Hint: Rear deletion moves pointer backward, not forward [OK]

Common Mistakes:

• Moving rear pointer forward instead of backward
• Not handling empty dequeue properly
• Confusing front and rear pointers

5. You want to implement a dequeue using a doubly linked list to support these operations efficiently:
1. Insert at front
2. Insert at rear
3. Delete from front
4. Delete from rear

Which of the following is the best approach to maintain pointers for O(1) time complexity for all operations?

hard

A. Maintain front and rear pointers; each node has next and prev links

B. Maintain only front pointer; traverse list for rear operations

C. Use singly linked list with only next pointers and rear pointer

D. Use array to simulate linked list with indices

Solution

1. Step 1: Understand operation requirements

   All operations must be O(1), so no traversal allowed.

2. Step 2: Analyze pointer needs

   Doubly linked list with front and rear pointers allows insert/delete at both ends in O(1).

3. Step 3: Check options

   Maintain front and rear pointers; each node has next and prev links matches this approach; others require traversal or use arrays which are not linked lists.

4. Final Answer:

   Maintain front and rear pointers; each node has next and prev links -> Option A

5. Quick Check:

   Doubly linked list + front/rear pointers = O(1) ops [OK]

Hint: Use doubly linked list with front and rear pointers [OK]

Common Mistakes:

• Using singly linked list causing O(n) rear operations
• Maintaining only one pointer causing traversal
• Confusing arrays with linked lists