Recursion is nothing but the process of calling of one function from the other only this process is done by calling of a function by itself. As we know when one function calls the other function the first function saves its state(its variables) and then passes the control to the called function. The called function can be called by using the same name of variables ex fun1(a) can call fun2(a). When we do recursive call nothing new happens. One function calls itself by passing the same type and similar in name variables(but obviously the values stored in variables are different,only the name remains same.)to itself. But before every call the function saves its state and this process of saving continues. The SAVING IS DONE ON A STACK.

现在堆栈开始发挥作用了。

因此，如果您编写了一个迭代程序，并每次将状态保存在堆栈上，然后在需要时从堆栈中弹出值，那么您已经成功地将递归程序转换为迭代程序!

证明是简单而分析的。

在递归中，计算机维护堆栈，而在迭代版本中，您将不得不手动维护堆栈。

仔细想想，只需将深度优先搜索(在图上)递归程序转换为dfs迭代程序。

祝你一切顺利!

Recursion is nothing but the process of calling of one function from the other only this process is done by calling of a function by itself. As we know when one function calls the other function the first function saves its state(its variables) and then passes the control to the called function. The called function can be called by using the same name of variables ex fun1(a) can call fun2(a). When we do recursive call nothing new happens. One function calls itself by passing the same type and similar in name variables(but obviously the values stored in variables are different,only the name remains same.)to itself. But before every call the function saves its state and this process of saving continues. The SAVING IS DONE ON A STACK.

现在堆栈开始发挥作用了。

因此，如果您编写了一个迭代程序，并每次将状态保存在堆栈上，然后在需要时从堆栈中弹出值，那么您已经成功地将递归程序转换为迭代程序!

证明是简单而分析的。

在递归中，计算机维护堆栈，而在迭代版本中，您将不得不手动维护堆栈。

仔细想想，只需将深度优先搜索(在图上)递归程序转换为dfs迭代程序。

祝你一切顺利!

实际上，最常见的方法是保留自己的堆栈。下面是一个C语言的递归快速排序函数:

void quicksort(int* array, int left, int right)
{
    if(left >= right)
        return;

    int index = partition(array, left, right);
    quicksort(array, left, index - 1);
    quicksort(array, index + 1, right);
}

以下是我们如何通过保持自己的堆栈来实现迭代:

void quicksort(int *array, int left, int right)
{
    int stack[1024];
    int i=0;

    stack[i++] = left;
    stack[i++] = right;

    while (i > 0)
    {
        right = stack[--i];
        left = stack[--i];

        if (left >= right)
             continue;

        int index = partition(array, left, right);
        stack[i++] = left;
        stack[i++] = index - 1;
        stack[i++] = index + 1;
        stack[i++] = right;
    }
}

显然，这个例子没有检查堆栈边界……实际上，你可以根据最坏的情况来确定堆栈的大小。但你懂的。

只是消磨时间……递归函数

void foo(Node* node)
{
    if(node == NULL)
       return;
    // Do something with node...
    foo(node->left);
    foo(node->right);
}

可转换为

void foo(Node* node)
{
    if(node == NULL)
       return;

    // Do something with node...

    stack.push(node->right);
    stack.push(node->left);

    while(!stack.empty()) {
         node1 = stack.pop();
         if(node1 == NULL)
            continue;
         // Do something with node1...
         stack.push(node1->right);             
         stack.push(node1->left);
    }

}

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)))))

似乎没有人指出递归函数在主体中调用自己超过一次的位置，并处理返回递归中的特定点(即不是原始递归)。据说每一个递归都可以转化为迭代，所以这似乎是可能的。

我刚刚想出了一个如何做到这一点的c#示例。假设您有以下递归函数，它的作用类似于poststorder遍历，AbcTreeNode是一个带有指针a、b、c的3元树。

public static void AbcRecursiveTraversal(this AbcTreeNode x, List<int> list) {
        if (x != null) {
            AbcRecursiveTraversal(x.a, list);
            AbcRecursiveTraversal(x.b, list);
            AbcRecursiveTraversal(x.c, list);
            list.Add(x.key);//finally visit root
        }
}

迭代解:

        int? address = null;
        AbcTreeNode x = null;
        x = root;
        address = A;
        stack.Push(x);
        stack.Push(null)    

        while (stack.Count > 0) {
            bool @return = x == null;

            if (@return == false) {

                switch (address) {
                    case A://   
                        stack.Push(x);
                        stack.Push(B);
                        x = x.a;
                        address = A;
                        break;
                    case B:
                        stack.Push(x);
                        stack.Push(C);
                        x = x.b;
                        address = A;
                        break;
                    case C:
                        stack.Push(x);
                        stack.Push(null);
                        x = x.c;
                        address = A;
                        break;
                    case null:
                        list_iterative.Add(x.key);
                        @return = true;
                        break;
                }

            }


            if (@return == true) {
                address = (int?)stack.Pop();
                x = (AbcTreeNode)stack.Pop();
            }


        }