LeetCode-in-All

160. Intersection of Two Linked Lists

Easy

Given the heads of two singly linked-lists headA and headB, return the node at which the two lists intersect. If the two linked lists have no intersection at all, return null.

For example, the following two linked lists begin to intersect at node c1:

The test cases are generated such that there are no cycles anywhere in the entire linked structure.

Note that the linked lists must retain their original structure after the function returns.

Custom Judge:

The inputs to the judge are given as follows (your program is not given these inputs):

• intersectVal - The value of the node where the intersection occurs. This is 0 if there is no intersected node.
• listA - The first linked list.
• listB - The second linked list.
• skipA - The number of nodes to skip ahead in listA (starting from the head) to get to the intersected node.
• skipB - The number of nodes to skip ahead in listB (starting from the head) to get to the intersected node.

The judge will then create the linked structure based on these inputs and pass the two heads, headA and headB to your program. If you correctly return the intersected node, then your solution will be accepted.

Example 1:

Input: intersectVal = 8, listA = [4,1,8,4,5], listB = [5,6,1,8,4,5], skipA = 2, skipB = 3

Output: Intersected at ‘8’

Explanation: The intersected node’s value is 8 (note that this must not be 0 if the two lists intersect). From the head of A, it reads as [4,1,8,4,5]. From the head of B, it reads as [5,6,1,8,4,5]. There are 2 nodes before the intersected node in A; There are 3 nodes before the intersected node in B.

Example 2:

Input: intersectVal = 2, listA = [1,9,1,2,4], listB = [3,2,4], skipA = 3, skipB = 1

Output: Intersected at ‘2’

Explanation: The intersected node’s value is 2 (note that this must not be 0 if the two lists intersect). From the head of A, it reads as [1,9,1,2,4]. From the head of B, it reads as [3,2,4]. There are 3 nodes before the intersected node in A; There are 1 node before the intersected node in B.

Example 3:

Input: intersectVal = 0, listA = [2,6,4], listB = [1,5], skipA = 3, skipB = 2

Output: No intersection

Explanation: From the head of A, it reads as [2,6,4]. From the head of B, it reads as [1,5]. Since the two lists do not intersect, intersectVal must be 0, while skipA and skipB can be arbitrary values. Explanation: The two lists do not intersect, so return null.

Constraints:

• The number of nodes of listA is in the m.
• The number of nodes of listB is in the n.
• 0 <= m, n <= 3 * 104
• 1 <= Node.val <= 105
• 0 <= skipA <= m
• 0 <= skipB <= n
• intersectVal is 0 if listA and listB do not intersect.
• intersectVal == listA[skipA] == listB[skipB] if listA and listB intersect.

Follow up: Could you write a solution that runs in O(n) time and use only O(1) memory?

Solution

import com_github_leetcode.ListNode;

/*
 * Definition for singly-linked list.
 * public class ListNode {
 *     int val;
 *     ListNode next;
 *     ListNode(int x) {
 *         val = x;
 *         next = null;
 *     }
 * }
 */
@SuppressWarnings("java:S2583")
public class Solution {
    public ListNode getIntersectionNode(ListNode headA, ListNode headB) {
        ListNode node1 = headA;
        ListNode node2 = headB;
        while (node1 != node2) {
            node1 = node1 == null ? headB : node1.next;
            node2 = node2 == null ? headA : node2.next;
        }
        return node1;
    }
}

Time Complexity (Big O Time):

The time complexity of this program is O(M + N), where M is the length of the first linked list (headA) and N is the length of the second linked list (headB). Here’s why:

• The two pointers node1 and node2 traverse their respective linked lists until they either meet at the intersection or reach the end of their lists.
• In the worst case, where there is no intersection, both node1 and node2 will traverse both linked lists completely.
• Therefore, each of the two pointers will perform a total of M + N operations (M for the first list and N for the second list).

The program terminates as soon as node1 and node2 meet or both become null.

Space Complexity (Big O Space):

The space complexity of this program is O(1), which means it uses a constant amount of extra space, regardless of the size of the linked lists. The program only uses a fixed number of pointers (node1, node2) and variables to keep track of the intersection point.

In summary, the time complexity is O(M + N) where M and N are the lengths of the two linked lists, and the space complexity is O(1), indicating a constant amount of additional memory usage.

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