"Swap Nodes in Pairs" is a problem typically found in the context of data structures, specifically linked lists. To explain this, let's start with the basics.
Linked List: A linked list is a linear data structure where each element (node) contains a value and a reference (or link) to the next node in the sequence. Unlike arrays, nodes in a linked list are not stored at contiguous memory locations; they are linked using pointers.
Node: Each element in a linked list is called a node. A typical node has two parts: data (value) and a pointer (reference to the next node).
Swapping Nodes: Swapping nodes involves changing the links or pointers so that the order of nodes is reversed for the pair. It doesn't involve swapping data between nodes.
Given a linked list, swap every two adjacent nodes and return its head. For example, if the linked list is 1->2->3->4
, the result after swapping in pairs should be 2->1->4->3
.
To solve this problem:
Iterative Approach:
Recursive Approach:
Let's assume a basic node structure:
class ListNode:
def __init__(self, value=0, next=None):
self.value = value
self.next = next
Here is how you might implement the swap:
def swapPairs(head):
# A dummy node to simplify edge cases like empty list or a list with single node
dummy = ListNode(0)
dummy.next = head
# Initialize the current node to start from dummy
current = dummy
while current.next and current.next.next:
# Nodes to be swapped
first = current.next
second = current.next.next
# Swapping
first.next = second.next
second.next = first
current.next = second
# Move to the next pair
current = current.next.next
# Return the new head of the list
return dummy.next
In this code:
dummy
node is a placeholder to handle edge cases.while current.next and current.next.next
).first
and second
are the two nodes in the current pair.next
pointers to swap first
and second
.current
to the next pair.This approach ensures that all pairs are swapped, handling both even and odd-length lists gracefully. The use of a dummy node simplifies edge cases, making the code more robust and easier to understand.