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。

//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;
}

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。)

你可以使用弗洛伊德的周期寻找算法，也被称为乌龟和野兔算法。 其思想是对列表有两个引用，并以不同的速度移动它们。一个向前移动1个节点，另一个向前移动2个节点。

如果链表有一个循环 一定会见面的。 或者 这两个引用(或下一个) 将变为null。

实现算法的Java函数:

boolean hasLoop(Node first) {

    if(first == null) // list does not exist..so no loop either
        return false;

    Node slow, fast; // create two references.

    slow = fast = first; // make both refer to the start of the list

    while(true) {

        slow = slow.next;          // 1 hop

        if(fast.next != null)
            fast = fast.next.next; // 2 hops
        else
            return false;          // next node null => no loop

        if(slow == null || fast == null) // if either hits null..no loop
            return false;

        if(slow == fast) // if the two ever meet...we must have a loop
            return true;
    }
}

这种方法有空间开销，但实现更简单:

循环可以通过在Map中存储节点来标识。在放置节点之前;检查节点是否已经存在。如果节点已经存在于映射中，则意味着链表有循环。

public boolean loopDetector(Node<E> first) {  
       Node<E> t = first;  
       Map<Node<E>, Node<E>> map = new IdentityHashMap<Node<E>, Node<E>>();  
       while (t != null) {  
            if (map.containsKey(t)) {  
                 System.out.println(" duplicate Node is --" + t  
                           + " having value :" + t.data);  

                 return true;  
            } else {  
                 map.put(t, t);  
            }  
            t = t.next;  
       }  
       return false;  
  }  

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.