检测链表中的循环可以用最简单的方法之一来完成，使用hashmap会导致O(N)复杂度，使用基于排序的方法会导致O(NlogN)复杂度。

当您从head开始遍历列表时，创建一个已排序的地址列表。当您插入一个新地址时，检查该地址是否已经在已排序的列表中，这需要O(logN)复杂度。

//链表查找循环函数

int findLoop(struct Node* head)
{
    struct Node* slow = head, *fast = head;
    while(slow && fast && fast->next)
    {
        slow = slow->next;
        fast = fast->next->next;
        if(slow == fast)
            return 1;
    }
 return 0;
}

public boolean hasLoop(Node start){   
   TreeSet<Node> set = new TreeSet<Node>();
   Node lookingAt = start;

   while (lookingAt.peek() != null){
       lookingAt = lookingAt.next;

       if (set.contains(lookingAt){
           return false;
        } else {
        set.put(lookingAt);
        }

        return true;
}   
// Inside our Node class:        
public Node peek(){
   return this.next;
}

请原谅我的无知(我对Java和编程仍然相当陌生)，但为什么上面的方法不能工作呢?

I guess this doesn't solve the constant space issue... but it does at least get there in a reasonable time, correct? It will only take the space of the linked list plus the space of a set with n elements (where n is the number of elements in the linked list, or the number of elements until it reaches a loop). And for time, worst-case analysis, I think, would suggest O(nlog(n)). SortedSet look-ups for contains() are log(n) (check the javadoc, but I'm pretty sure TreeSet's underlying structure is TreeMap, whose in turn is a red-black tree), and in the worst case (no loops, or loop at very end), it will have to do n look-ups.

func checkLoop(_ head: LinkedList) -> Bool {
    var curr = head
    var prev = head
    
    while curr.next != nil, curr.next!.next != nil {
        curr = (curr.next?.next)!
        prev = prev.next!
        
        if curr === prev {
            return true
        }
    }
    
    return false
}

我可能会非常晚和新的处理这个线程。但还是. .

为什么不能将节点的地址和“下一个”节点指向存储在表中

如果我们可以这样做

node present: (present node addr) (next node address)

node 1: addr1: 0x100 addr2: 0x200 ( no present node address till this point had 0x200)
node 2: addr2: 0x200 addr3: 0x300 ( no present node address till this point had 0x300)
node 3: addr3: 0x300 addr4: 0x400 ( no present node address till this point had 0x400)
node 4: addr4: 0x400 addr5: 0x500 ( no present node address till this point had 0x500)
node 5: addr5: 0x500 addr6: 0x600 ( no present node address till this point had 0x600)
node 6: addr6: 0x600 addr4: 0x400 ( ONE present node address till this point had 0x400)

这样就形成了一个循环。

在这个上下文中，到处都有文本材料的加载。我只是想张贴一个图表表示，真正帮助我掌握概念。

当快、慢在点p相遇时，

快速行进的距离= a+b+c+b = a+2b+c

慢行距离= a+b

因为快的比慢的快2倍。 所以a+2b+c = 2(a+b)然后得到a=c。

因此，当另一个慢指针再次从头部运行到q时，同时，快速指针将从p运行到q，因此它们在q点会合。

public ListNode detectCycle(ListNode head) {
    if(head == null || head.next==null)
        return null;

    ListNode slow = head;
    ListNode fast = head;

    while (fast!=null && fast.next!=null){
        fast = fast.next.next;
        slow = slow.next;

        /*
        if the 2 pointers meet, then the 
        dist from the meeting pt to start of loop 
        equals
        dist from head to start of loop
        */
        if (fast == slow){ //loop found
            slow = head;
            while(slow != fast){
                slow = slow.next;
                fast = fast.next;
            }
            return slow;
        }            
    }
    return null;
}