Given the head
of a singly linked list, return true
if it is a palindrome.
Example 1:
Input: head = [1,2,2,1] Output: true
Example 2:
Input: head = [1,2] Output: false
Constraints:
[1, 105]
.0 <= Node.val <= 9
Follow up: Could you do it in
O(n)
time and O(1)
space?The core challenge of this problem is to determine if the values in a singly linked list form a palindrome. A palindrome is a sequence that reads the same backward as forward. This problem is significant in various applications such as text processing, data validation, and more.
Potential pitfalls include handling edge cases like an empty list or a list with a single node, and ensuring the solution is efficient in both time and space.
To solve this problem, we can consider the following approaches:
A naive solution would involve copying the linked list values into an array or list, and then checking if the array is a palindrome. This approach, however, uses O(n) space, which is not optimal.
To achieve O(n) time complexity and O(1) space complexity, we can use the following approach:
Let's break down the algorithm step-by-step:
class ListNode {
int val;
ListNode next;
ListNode(int x) { val = x; }
}
public class Solution {
public boolean isPalindrome(ListNode head) {
if (head == null || head.next == null) return true;
// Step 1: Find the middle of the linked list
ListNode slow = head, fast = head;
while (fast != null && fast.next != null) {
slow = slow.next;
fast = fast.next.next;
}
// Step 2: Reverse the second half of the linked list
ListNode prev = null, curr = slow, next = null;
while (curr != null) {
next = curr.next;
curr.next = prev;
prev = curr;
curr = next;
}
// Step 3: Compare the first half and the reversed second half
ListNode firstHalf = head, secondHalf = prev;
while (secondHalf != null) {
if (firstHalf.val != secondHalf.val) return false;
firstHalf = firstHalf.next;
secondHalf = secondHalf.next;
}
// Optional Step 4: Restore the list (not required for the problem)
// Reverse the second half again to restore the original list structure
return true;
}
}
The time complexity of this approach is O(n) because we traverse the list a constant number of times. The space complexity is O(1) because we only use a few extra pointers, regardless of the list size.
Consider the following edge cases:
To test the solution comprehensively, consider the following test cases:
When approaching such problems, consider the following tips:
In this blog post, we discussed how to determine if a singly linked list is a palindrome using an efficient approach with O(n) time complexity and O(1) space complexity. Understanding and solving such problems is crucial for improving your algorithmic thinking and coding skills.
For further reading and practice, consider the following resources: