在我多年的编程生涯中,我经常使用递归来解决简单的问题,但我完全意识到,有时由于内存/速度问题,您需要迭代。
所以,在很久以前的某个时候,我去尝试寻找是否存在任何“模式”或教科书上的方法来将常见的递归方法转换为迭代,但一无所获。至少我想不起有什么帮助。
有一般的规则吗? 有“模式”吗?
在我多年的编程生涯中,我经常使用递归来解决简单的问题,但我完全意识到,有时由于内存/速度问题,您需要迭代。
所以,在很久以前的某个时候,我去尝试寻找是否存在任何“模式”或教科书上的方法来将常见的递归方法转换为迭代,但一无所获。至少我想不起有什么帮助。
有一般的规则吗? 有“模式”吗?
当前回答
This is an old question but I want to add a different aspect as a solution. I'm currently working on a project in which I used the flood fill algorithm using C#. Normally, I implemented this algorithm with recursion at first, but obviously, it caused a stack overflow. After that, I changed the method from recursion to iteration. Yes, It worked and I was no longer getting the stack overflow error. But this time, since I applied the flood fill method to very large structures, the program was going into an infinite loop. For this reason, it occurred to me that the function may have re-entered the places it had already visited. As a definitive solution to this, I decided to use a dictionary for visited points. If that node(x,y) has already been added to the stack structure for the first time, that node(x,y) will be saved in the dictionary as the key. Even if the same node is tried to be added again later, it won't be added to the stack structure because the node is already in the dictionary. Let's see on pseudo-code:
startNode = pos(x,y)
Stack stack = new Stack();
Dictionary visited<pos, bool> = new Dictionary();
stack.Push(startNode);
while(stack.count != 0){
currentNode = stack.Pop();
if "check currentNode if not available"
continue;
if "check if already handled"
continue;
else if "run if it must be wanted thing should be handled"
// make something with pos currentNode.X and currentNode.X
// then add its neighbor nodes to the stack to iterate
// but at first check if it has already been visited.
if(!visited.Contains(pos(x-1,y)))
visited[pos(x-1,y)] = true;
stack.Push(pos(x-1,y));
if(!visited.Contains(pos(x+1,y)))
...
if(!visited.Contains(pos(x,y+1)))
...
if(!visited.Contains(pos(x,y-1)))
...
}
其他回答
一个被关闭为这个问题的副本的问题有一个非常特定的数据结构:
节点结构如下:
typedef struct {
int32_t type;
int32_t valueint;
double valuedouble;
struct cNODE *next;
struct cNODE *prev;
struct cNODE *child;
} cNODE;
递归删除函数如下所示:
void cNODE_Delete(cNODE *c) {
cNODE*next;
while (c) {
next=c->next;
if (c->child) {
cNODE_Delete(c->child)
}
free(c);
c=next;
}
}
一般来说,对于多次(甚至一次)调用自身的递归函数,避免使用堆栈并不总是可能的。然而,对于这种特殊的结构,这是可能的。其思想是将所有节点平展为单个列表。这是通过将当前节点的子节点放在顶部行列表的末尾来实现的。
void cNODE_Delete (cNODE *c) {
cNODE *tmp, *last = c;
while (c) {
while (last->next) {
last = last->next; /* find last */
}
if ((tmp = c->child)) {
c->child = NULL; /* append child to last */
last->next = tmp;
tmp->prev = last;
}
tmp = c->next; /* remove current */
free(c);
c = tmp;
}
}
这种技术可以应用于任何可以简化为具有确定性拓扑顺序的DAG的数据链接结构。当前节点子节点被重新排列,以便最后一个子节点采用所有其他子节点。然后可以删除当前节点,然后遍历可以迭代到剩余的子节点。
要寻找的一种模式是函数末尾的递归调用(所谓的尾部递归)。这很容易用一段时间来代替。例如,函数foo:
void foo(Node* node)
{
if(node == NULL)
return;
// Do something with node...
foo(node->left);
foo(node->right);
}
以调用foo结束。这可以替换为:
void foo(Node* node)
{
while(node != NULL)
{
// Do something with node...
foo(node->left);
node = node->right;
}
}
这消除了第二次递归调用。
通常,通过将通常传递给递归函数的参数推入堆栈,我将递归算法替换为迭代算法。事实上,您正在用自己的程序堆栈替换程序堆栈。
var stack = [];
stack.push(firstObject);
// while not empty
while (stack.length) {
// Pop off end of stack.
obj = stack.pop();
// Do stuff.
// Push other objects on the stack as needed.
...
}
注意:如果你在里面有多个递归调用,并且你想要保留调用的顺序,你必须以相反的顺序将它们添加到堆栈:
foo(first);
foo(second);
必须由
stack.push(second);
stack.push(first);
编辑:文章堆栈和递归消除(或文章备份链接)详细介绍了这个主题。
一般来说,通过简单地使用存储变量,可以将递归模拟为迭代。注意,递归和迭代通常是等价的;其中一种几乎总是可以转化为另一种。尾递归函数很容易转化为迭代函数。只需要将累加器变量设置为局部变量,并迭代而不是递归。下面是c++中的一个例子(如果不使用默认参数的话):
// tail-recursive
int factorial (int n, int acc = 1)
{
if (n == 1)
return acc;
else
return factorial(n - 1, acc * n);
}
// iterative
int factorial (int n)
{
int acc = 1;
for (; n > 1; --n)
acc *= n;
return acc;
}
据我所知,我可能在代码中犯了一个错误,但想法是存在的。
我的例子是用Clojure编写的,但是应该很容易翻译成任何语言。
给定这个函数,当n值较大时StackOverflows:
(defn factorial [n]
(if (< n 2)
1
(*' n (factorial (dec n)))))
我们可以用以下方式定义一个使用自己堆栈的版本:
(defn factorial [n]
(loop [n n
stack []]
(if (< n 2)
(return 1 stack)
;; else loop with new values
(recur (dec n)
;; push function onto stack
(cons (fn [n-1!]
(*' n n-1!))
stack)))))
其中return定义为:
(defn return
[v stack]
(reduce (fn [acc f]
(f acc))
v
stack))
这也适用于更复杂的函数,例如阿克曼函数:
(defn ackermann [m n]
(cond
(zero? m)
(inc n)
(zero? n)
(recur (dec m) 1)
:else
(recur (dec m)
(ackermann m (dec n)))))
可以转化为:
(defn ackermann [m n]
(loop [m m
n n
stack []]
(cond
(zero? m)
(return (inc n) stack)
(zero? n)
(recur (dec m) 1 stack)
:else
(recur m
(dec n)
(cons #(ackermann (dec m) %)
stack)))))