Question: Given a linked list, return the node where the cycle begins. If there is no cycle, return null.
Output: 0
The easier method to find the cycle has been discussed in this post.
This method is based upon the idea of a circular race track. If there is a slow runner and a fast runner, eventually the fast runner will catch up the slow runner from behind. A similar analogy can be applied to a tortoise and a hare and hence the method is also called Tortoise and Hare method or the Floyd-Warshal algorithm.
The method is divided into 2 steps.
STEP 1: Determine if there is a loop.
The first phase/step of this method is to determine if there is actually any loop in the Linked List. If no loop is found, then we need to directly return null.
STEP 2: Find the loop.
- We initialize 2 pointers. Fast(hare) and slow(tortoise).
- Advance slow pointer by 1 step. Advance fast pointer by 2 steps.
- Keep performing the above step in a loop until both the pointers meet.
- As soon as they meet, start one more pointer from the beginning of the list.
- Move the slow pointer and the new pointer one step at a time.
- The place where they meet is the point where the loop starts in the linked list.
To have a better understanding of why this method works, have a look at the following image.
- Both hare and tortoise start from POINT 1.
- The hare covers distance ‘F’ enters the loop and starts moving in the loop at POINT 2.
- The hare runs for a while as he is fast and moves on path ‘a’.
- The tortoise now enters the loop at POINT 2 after covering ‘F’ and keeps on moving on path ‘a’. While the hare is now on path ‘b’.
- The tortoise keeps on moving on path ‘a’ and the hare eventually catches up with the tortoise at POINT 3.
- Start a new pointer from POINT 1 and it runs at the same speed of tortoise.
We know that speed of hare is double the speed of tortoise.
Let us look at a little math now:-
2 * distance(tortoise) = distance(hare)
2 * (F + a) = F + a + b + a
2F + 2a = F + 2a + b
F = b
Hence POINT 2 is the point where loop starts.
The source-code for the above algorithm is given below.
// Template for a linked list node
class ListNode {
int value;
ListNode next;
}
public class Solution {
private ListNode getIntersect(ListNode head) {
ListNode tortoise = head;
ListNode hare = head;
// A fast pointer will either loop around a cycle and meet the slow
// pointer or reach the `null` at the end of a non-cyclic list.
while (hare != null && hare.next != null) {
tortoise = tortoise.next;
hare = hare.next.next;
if (tortoise == hare) {
return tortoise;
}
}
return null;
}
public ListNode detectCycle(ListNode head) {
if (head == null) {
return null;
}
// If there is a cycle, the fast/slow pointers will intersect at some
// node. Otherwise, there is no cycle, so we cannot find an entrance to
// a cycle.
ListNode intersect = getIntersect(head);
if (intersect == null) {
return null;
}
// To find the entrance to the cycle, we have two pointers traverse at
// the same speed -- one from the front of the list, and the other from
// the point of intersection.
ListNode ptr1 = head;
ListNode ptr2 = intersect;
while (ptr1 != ptr2) {
ptr1 = ptr1.next;
ptr2 = ptr2.next;
}
return ptr1;
}
}
Code language: Java (java)
Time Complexity: O(n)
Space Complexity: O(1)
A sample problem can be found here.