Given a singly linked list containing n nodes. The problem is to sort the list using the recursive selection sort technique. The approach should be such that it involves swapping node links instead of swapping node data.

Examples:
Input: 10 -> 12 -> 8 -> 4 -> 6 Output: 4 -> 6 -> 8 -> 10 -> 12
In Selection Sort, we first find the minimum element, swap it with the beginning node and recur for the remaining list. Below is the recursive implementation of these steps for the linked list.
recurSelectionSort(head)
if head->next == NULL
return head
Initialize min = head
Initialize beforeMin = NULL
Initialize ptr = head
while ptr->next != NULL
if min->data > ptr->next->data
min = ptr->next
beforeMin = ptr
ptr = ptr->next
if min != head
swapNodes(&head, head, min, beforeMin)
head->next = recurSelectionSort(head->next)
return head
swapNodes(head_ref, currX, currY, prevY)
head_ref = currY
prevY->next = currX
Initialize temp = currY->next
currY->next = currX->next
currX->next = temp
The swapNodes(head_ref, currX, currY, prevY) is based on the approach discussed here but it has been modified accordingly for the implementation of this post.
# Python implementation of recursive
# selection sort for singly linked
# list | Swapping node links
# Linked List node
class Node:
def __init__(self, data):
self.data = data
self.next = None
# Function to swap nodes 'currX' and
# 'currY' in a linked list without
# swapping data
def swapNodes(head_ref, currX,
currY, prevY):
# Make 'currY' as new head
head_ref = currY
# Adjust links
prevY.next = currX
# Swap next pointers
temp = currY.next
currY.next = currX.next
currX.next = temp
return head_ref
# Function to sort the linked list using
# recursive selection sort technique
def recurSelectionSort(head):
# If there is only a single node
if (head.next == None):
return head
# 'min' - pointer to store the node
# having minimum data value
min = head
# 'beforeMin' - pointer to store node
# previous to 'min' node
beforeMin = None
ptr = head
# Traverse the list till the last node
while (ptr.next != None):
# if true, then update 'min' and
# 'beforeMin'
if (ptr.next.data < min.data) :
min = ptr.next
beforeMin = ptr
ptr = ptr.next
# if 'min' and 'head' are not same,
# swap the head node with the 'min' node
if (min != head):
head = swapNodes(head, head,
min, beforeMin)
# Recursively sort the remaining list
head.next = recurSelectionSort(head.next)
return head
# Function to sort the given linked list
def sort(head_ref):
# If list is empty
if ((head_ref) == None):
return None
# Sort the list using recursive
# selection sort technique
head_ref = recurSelectionSort(head_ref)
return head_ref
# Function to insert a node at the
# beginning of the linked list
def push(head_ref, new_data):
# Allocate node
new_node = Node(0)
# Put in the data
new_node.data = new_data
# Link the old list to the
# new node
new_node.next = (head_ref)
# Move the head to point to the
# new node
(head_ref) = new_node
return head_ref
# Function to print the linked list
def printList(head):
while (head != None):
print(head.data , end = " ")
head = head.next
# Driver code
head = None
# Create linked list 10.12.8.4.6
head = push(head, 6)
head = push(head, 4)
head = push(head, 8)
head = push(head, 12)
head = push(head, 10)
print("Linked list before sorting:")
printList(head)
# sort the linked list
head = sort(head)
print("\nLinked list after sorting:")
printList(head)
# This code is contributed by Arnab Kundu
# This code is modified by Susobhan Akhuli
Output
Linked list before sorting: 10 12 8 4 6 Linked list after sorting: 4 6 8 10 12
Time Complexity: O(n2), since we are traversing the linked list using a while loop and inside it there is a recursive function is operating at O(n) time thus the complexity turns out to be quadratic
Auxiliary Space: O(n), since we are using recursion all elements in the linked List takes up the entire stack space
Please refer complete article on Recursive selection sort for singly linked list | Swapping node links for more details!