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)))))

另一个使用堆栈将递归函数转换为迭代函数的简单而完整的示例。

#include <iostream>
#include <stack>
using namespace std;

int GCD(int a, int b) { return b == 0 ? a : GCD(b, a % b); }

struct Par
{
    int a, b;
    Par() : Par(0, 0) {}
    Par(int _a, int _b) : a(_a), b(_b) {}
};

int GCDIter(int a, int b)
{
    stack<Par> rcstack;

    if (b == 0)
        return a;
    rcstack.push(Par(b, a % b));

    Par p;
    while (!rcstack.empty()) 
    {
        p = rcstack.top();
        rcstack.pop();
        if (p.b == 0)
            continue;
        rcstack.push(Par(p.b, p.a % p.b));
    }

    return p.a;
}

int main()
{
    //cout << GCD(24, 36) << endl;
    cout << GCDIter(81, 36) << endl;

    cin.get();
    return 0;
}

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)))))

想想那些真正需要堆栈的东西:

如果我们考虑递归的模式为:

if(task can be done directly) {
    return result of doing task directly
} else {
    split task into two or more parts
    solve for each part (possibly by recursing)
    return result constructed by combining these solutions
}

例如，经典的河内塔

if(the number of discs to move is 1) {
    just move it
} else {
    move n-1 discs to the spare peg
    move the remaining disc to the target peg
    move n-1 discs from the spare peg to the target peg, using the current peg as a spare
}

这可以转化为一个循环工作在一个显式的堆栈，通过重申它为:

place seed task on stack
while stack is not empty 
   take a task off the stack
   if(task can be done directly) {
      Do it
   } else {
      Split task into two or more parts
      Place task to consolidate results on stack
      Place each task on stack
   }
}

对于《河内塔》来说，这就变成了:

stack.push(new Task(size, from, to, spare));
while(! stack.isEmpty()) {
    task = stack.pop();
    if(task.size() = 1) {
        just move it
    } else {
        stack.push(new Task(task.size() -1, task.spare(), task,to(), task,from()));
        stack.push(new Task(1, task.from(), task.to(), task.spare()));
        stack.push(new Task(task.size() -1, task.from(), task.spare(), task.to()));
    }
}

在如何定义堆栈方面，这里有相当大的灵活性。你可以让你的堆栈成为一个Command对象列表，这些对象可以做一些复杂的事情。或者你可以走相反的方向，让它成为一个简单类型的列表(例如，一个“task”可能是一个int堆栈上的4个元素，而不是一个task堆栈上的一个元素)。

这意味着堆栈的内存在堆中，而不是在Java执行堆栈中，但这可能很有用，因为您可以更好地控制它。

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!