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。

我不确定这个答案是否适用于Java，但我仍然认为它属于这里:

当我们在现代体系结构中使用指针时，我们可以期望它们是CPU字对齐的。对于64位体系结构，这意味着指针的前3位始终为零。这让我们可以使用这个内存来标记我们已经见过的指针，通过对它们的第一个比特写入1。

如果我们遇到一个指针，它的第一个位已经写了1，那么我们已经成功地找到了一个循环，之后我们需要再次遍历结构，并将这些位屏蔽掉。完成了!

这种方法被称为指针标记，它在低级编程中被过度使用，例如Haskell在一些优化中使用它。

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。

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);
}