Reverse a Singly Linked List Recursive in DSA Python - Time & Space Complexity

Time Complexity: Reverse a Singly Linked List Recursive

O(n)

Understanding Time Complexity

When reversing a singly linked list using recursion, we want to know how the time needed grows as the list gets longer.

We ask: How many steps does it take to reverse a list of size n?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

class Node:
    def __init__(self, val):
        self.val = val
        self.next = None

def reverse_recursive(head):
    if head is None or head.next is None:
        return head
    new_head = reverse_recursive(head.next)
    head.next.next = head
    head.next = None
    return new_head

This code reverses a singly linked list by calling itself on the next node until it reaches the end, then rewires the links backward.

Identify Repeating Operations

• Primary operation: Recursive call on each node of the list.
• How many times: Exactly once per node, so n times for a list of size n.

How Execution Grows With Input

Each node causes one recursive call, so the total steps grow directly with the number of nodes.

Input Size (n)	Approx. Operations
10	About 10 recursive calls and rewiring steps
100	About 100 recursive calls and rewiring steps
1000	About 1000 recursive calls and rewiring steps

Pattern observation: The work grows linearly as the list size increases.

Final Time Complexity

Time Complexity: O(n)

This means the time to reverse the list grows in direct proportion to the number of nodes.

Common Mistake

[X] Wrong: "Recursion makes this slower than a loop, so it must be more than O(n)."

[OK] Correct: Each node is still visited once, so recursion does not add extra visits; it just changes how the calls are made.

Interview Connect

Understanding recursive reversal shows you can think about problems in different ways and handle linked lists confidently, a key skill in many coding challenges.

Self-Check

"What if we changed the recursion to an iterative loop? How would the time complexity change?"

Practice

1. What does the recursive function to reverse a singly linked list primarily do at each step?

easy

A. It iterates through the list using a loop to reverse pointers.

B. It swaps the values of the first and last nodes only.

C. It reverses the rest of the list and then adjusts the current node's next pointer.

D. It creates a new list and copies nodes in reverse order.

Solution

1. Step 1: Understand recursion on linked list

   The function calls itself on the next node until it reaches the end (base case).

2. Step 2: Reverse pointers on return

   After reaching the end, it reverses the next pointer of the current node to point backward.

3. Final Answer:

   It reverses the rest of the list and then adjusts the current node's next pointer. -> Option C

4. Quick Check:

   Recursive reversal = reverse rest + fix pointers [OK]

Hint: Think: reverse rest first, then fix current pointer [OK]

Common Mistakes:

• Trying to swap node values instead of pointers
• Using loops instead of recursion
• Not handling the base case properly

2. Which of the following is the correct base case for a recursive function reversing a singly linked list?

easy

A. if head.next is None: return None

B. if head.next is None: return head.next

C. if head is None: return head.next

D. if head is None or head.next is None: return head

Solution

1. Step 1: Identify base case meaning

   The base case stops recursion when the list is empty or has one node.

2. Step 2: Check correct condition

   When head is None (empty) or head.next is None (single node), return head as reversed list.

3. Final Answer:

   if head is None or head.next is None: return head -> Option D

4. Quick Check:

   Base case = empty or single node [OK]

Hint: Base case: empty or single node returns itself [OK]

Common Mistakes:

• Returning None incorrectly for single node
• Missing the empty list check
• Returning head.next instead of head

3. What will be the output linked list after reversing recursively the list: 1 -> 2 -> 3 -> None?

medium

A. 1 -> 2 -> 3 -> None

B. 3 -> 2 -> 1 -> None

C. 2 -> 3 -> 1 -> None

D. None -> 3 -> 2 -> 1

Solution

1. Step 1: Trace recursive calls

   Function calls itself on 2 -> 3 -> None, then on 3 -> None (base case).

2. Step 2: Reverse pointers on return

   On return, 3 points to 2, 2 points to 1, and 1 points to None.

3. Final Answer:

   3 -> 2 -> 1 -> None -> Option B

4. Quick Check:

   Reversed list = 3 -> 2 -> 1 [OK]

Hint: Last node becomes new head after recursion [OK]

Common Mistakes:

• Not updating the last node's next pointer
• Returning original head instead of new head
• Confusing node values with pointers

4. Given this recursive reverse function, what is the error?

def reverse(head):
    if head is None:
        return None
    new_head = reverse(head.next)
    head.next.next = head
    head.next = None
    return new_head

medium

A. Base case misses single node check causing AttributeError

B. head.next.next = head causes infinite loop

C. head.next = None should be before recursive call

D. Function returns None always

Solution

1. Step 1: Analyze base case

   Base case only checks if head is None, but not if head.next is None (single node).

2. Step 2: Identify error cause

   When head.next is None, head.next.next causes AttributeError because head.next is None.

3. Final Answer:

   Base case misses single node check causing AttributeError -> Option A

4. Quick Check:

   Missing single node base case = error [OK]

Hint: Always check head.next is None in base case [OK]

Common Mistakes:

• Ignoring single node base case
• Changing pointers before recursion
• Returning None instead of new head

5. How would you modify the recursive reverse function to also return the tail node of the reversed list efficiently?

hard

A. Return a tuple (new_head, tail) and update tail during recursion

B. Use a global variable to track tail node

C. Traverse the reversed list again to find tail after recursion

D. Return only new_head and ignore tail

Solution

1. Step 1: Understand tail tracking need

   To get tail efficiently, return it along with new head during recursion.

2. Step 2: Modify function to return tuple

   Return (new_head, tail) from recursive calls and update tail as current node.

3. Step 3: Avoid extra traversal

   This avoids traversing reversed list again, improving efficiency.

4. Final Answer:

   Return a tuple (new_head, tail) and update tail during recursion -> Option A

5. Quick Check:

   Return (head, tail) tuple for efficiency [OK]

Hint: Return both head and tail as tuple in recursion [OK]

Common Mistakes:

• Using global variables causing side effects
• Traversing list again after reversal
• Ignoring tail node requirement