如果允许我们嵌入类Node，我将像下面实现的那样解决这个问题。hasLoop()在O(n)时间内运行，并且只占用计数器的空间。这是不是一个合适的解决方案?或者是否有一种不嵌入Node的方法?(显然，在真正的实现中会有更多的方法，如RemoveNode(Node n)等。)

public class LinkedNodeList {
    Node first;
    Int count;

    LinkedNodeList(){
        first = null;
        count = 0;
    }

    LinkedNodeList(Node n){
        if (n.next != null){
            throw new error("must start with single node!");
        } else {
            first = n;
            count = 1;
        }
    }

    public void addNode(Node n){
        Node lookingAt = first;

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

        lookingAt.next = n;
        count++;
    }

    public boolean hasLoop(){

        int counter = 0;
        Node lookingAt = first;

        while(lookingAt.next != null){
            counter++;
            if (count < counter){
                return false;
            } else {
               lookingAt = lookingAt.next;
            }
        }

        return true;

    }



    private class Node{
        Node next;
        ....
    }

}

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.

乌龟和兔子

看看波拉德的算法。这不是完全相同的问题，但也许你会理解其中的逻辑，并将其应用于链表。

(如果你很懒，你可以看看周期检测——看看关于乌龟和兔子的那部分。)

这只需要线性时间和2个额外的指针。

在Java中:

boolean hasLoop( Node first ) {
    if ( first == null ) return false;

    Node turtle = first;
    Node hare = first;

    while ( hare.next != null && hare.next.next != null ) {
         turtle = turtle.next;
         hare = hare.next.next;

         if ( turtle == hare ) return true;
    }

    return false;
}

(大多数解决方案不会同时检查next和next。接下来是null。此外，因为乌龟总是在后面，你不需要检查它是否为空——兔子已经检查过了。)

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;
}

下面的方法可能不是最好的——它是O(n²)。然而，它应该有助于完成工作(最终)。

count_of_elements_so_far = 0;
for (each element in linked list)
{
    search for current element in first <count_of_elements_so_far>
    if found, then you have a loop
    else,count_of_elements_so_far++;
}

乌龟和兔子的另一种解决方案，不太好，因为我暂时改变了列表:

这个想法是遍历列表，并在执行过程中反转它。然后，当你第一次到达一个已经被访问过的节点时，它的next指针将指向“向后”，导致迭代再次朝第一个方向进行，并在那里终止。

Node prev = null;
Node cur = first;
while (cur != null) {
    Node next = cur.next;
    cur.next = prev;
    prev = cur;
    cur = next;
}
boolean hasCycle = prev == first && first != null && first.next != null;

// reconstruct the list
cur = prev;
prev = null;
while (cur != null) {
    Node next = cur.next;
    cur.next = prev;
    prev = cur;
    cur = next;
}

return hasCycle;

测试代码:

static void assertSameOrder(Node[] nodes) {
    for (int i = 0; i < nodes.length - 1; i++) {
        assert nodes[i].next == nodes[i + 1];
    }
}

public static void main(String[] args) {
    Node[] nodes = new Node[100];
    for (int i = 0; i < nodes.length; i++) {
        nodes[i] = new Node();
    }
    for (int i = 0; i < nodes.length - 1; i++) {
        nodes[i].next = nodes[i + 1];
    }
    Node first = nodes[0];
    Node max = nodes[nodes.length - 1];

    max.next = null;
    assert !hasCycle(first);
    assertSameOrder(nodes);
    max.next = first;
    assert hasCycle(first);
    assertSameOrder(nodes);
    max.next = max;
    assert hasCycle(first);
    assertSameOrder(nodes);
    max.next = nodes[50];
    assert hasCycle(first);
    assertSameOrder(nodes);
}