Loops in Lisp Part 1: Goto

At its core, Common Lisp provides two primitives for performing iteration. The first of those primitives is recursion. Recursion is an amazing technique, but in this post I am going to focus on the other primitive – goto.

Goto is extremely powerful. It lets you manipulate the control flow of your program in anyway you can think of. This freedom to do whatever you want is also what makes goto so dangerous. In any given piece of code that uses goto, it is difficult to tell what the purpose of the goto is because it could be used for so many different reasons. Because of this, most languages provide various kinds of builtin loops instead of providing raw goto. Even though loops aren’t as general as goto, they express the intention of the code much more clearly.

As an example, let’s say you want to print all of the characters in a file. If your language provided while loops, you could do this by printing characters from the file one at a time while there are more characters left. If Common Lisp had while loops,1 the code for this procedure would look like this:

(while (peek-char file nil nil)
  (write-char (read-char file)))

If your language only had goto, it becomes much more difficult to implement the procedure. In the end, you have to, in some way, simulate a while loop. One way to code the procedure with just goto is the following. First check if there are any characters left in the file. If there aren’t any, goto the end. Otherwise print the next character and go back to the start. Here is Common Lisp code that implements this:2

  (if (not (peek-char file nil nil))
      (go end))
  (write-char (read-char file))
  (go start)

Not only is the version with goto much more verbose, it is also much harder to understand. The code lacks clarity because goto is so general. It gives you no context into how it is being used. The reader of the code will have to think about the positioning of all of the gotos before they can think about the overall flow of the program. On the other hand, in the version with the while loop, merely the fact that a while loop is being used gives whoever is reading the code a decent idea of the control flow.

In reality all loops are eventually compiled down to gotos. Whenever the compiler for a language that provides loops sees a loop, it generates code that simulates the loop through goto. You can do the same thing with Lisp macros!

If you don’t know, Lisp macros are compile time functions which take code as their input and return code as their output. When Lisp code is being compiled, all of the macros in the code are called and each one is replaced with its result. This means you can write a macro that looks like a while loop when you use it, but at compile time generates code to simulate a while loop through goto. You are in effect adding while loops to the Lisp compiler! Here is code that defines such a macro:

(defmacro while (test &body body)
  (let ((gtop (gensym))
        (gend (gensym)))
       (if (not ,test)
           (go ,gend))
       (go ,gtop)

With this macro, the first code example is now valid lisp code! The while macro takes as arguments a test and a body. It then generates code that uses the method used in the second example to simulate a while loop with goto. You can actually see what the first example looks like after expanding the macro by using the function macroexpand. Here is what the generated code looks like:

  (if (not (peek-char file nil nil))
      (go #:g730))
  (write-char (read-char file))
  (go #:g729)

The generated code is the exact same as the code in the second example except for the names of the labels. This means the two examples are the same functionally! The only real difference between them is that the first one is expressed in terms of loops, and the second one is expressed in terms of goto. Since it is so much easier to think in terms of loops than goto, there is no reason why you wouldn’t use the first example over the second.

Macros allow you to build any feature you want as long as it is possible to simulate that feature through lower level features. With respect to goto, this means you can build any kind of control flow construct you want by simulating it with goto and then putting a macro on top. In Common Lisp, all of the looping constructs (do, do*, dotimes, dolist, loop) are really just macros that expand into goto. This is what Alan Kay meant when he said “Lisp isn’t a language, it’s a building material”. It bears repeating. In Lisp, you can build any feature you want as long as it is possible to simulate that feature in terms of lower level features.


In my last post I talked about memoization i.e. caching the results of a function. Memoization is a fairly common technique for optimization. It is common enough to warrant writing a macro that makes it easy to define memoized functions. When demonstrating memoization, I had a memoized Fibonacci function that looked like this:1

(let ((table (make-hash-table)))
  (defun fib (n)
    (or (gethash n table)
        (setf (gethash n table)
              (if (<= 0 n 1)
                  (+ (fib (- n 1))
                     (fib (- n 2))))))))

There are a couple problems with the above code. One problem is the boilerplate. If you wanted ten different memoized functions, you would have to copy lines 1, 3, and 4 for every single memoized function. Some people like to call programmers who do this needless duplication, “human compilers”, since they are writing code that the compiler should be writing for them.

Another issue with the above code is the lack of abstraction. If you wanted to change the caching mechanism to say, only cache the last hundred values, you would have to change the definition of every single function! Ideally you would only need to modify the code in one place in order to change how the caching is implemented.

Defmemo is one way to solve both of these problems. Here is what the above code would look like if it were were to use defmemo:

(defmemo fib (n)
  (if (<= 0 n 1)
      (+ (fib (- n 1))
         (fib (- n 2)))))

Defmemo solves both of the problems extremely well. It removes all of the differences between the memoized version on the regular version except for having to use “defmemo” instead of “defun”. Defmemo also solves the abstraction problem by moving all of the code relevant to memoization into the body of defmemo. If you want to change how memoization works, all you have to do is change the code for defmemo.

Now for the implementation of defmemo. The implementation is made up of two separate parts. First, a higher order function, memo, which takes a function as an argument, and returns a memoized version of that function. The second part is the actual macro, defmemo. Instead of just defining the function like defun, defmemo first builds a lambda expression for the body. Then it generates code that calls memo on that lambda function. Finally defmemo uses the result of memo as the implementation of the function being defined.2

Here is the code for memo:34

(defun memo (f)
  (let ((cache (make-hash-table :test #'equalp)))
    (lambda (&rest args)
      (or (gethash args cache)
          (setf (gethash args cache)
                (apply f args))))))

Memo works by returning a function that has an internal hash-table. When that function is called, it first checks its hash-table to see if it has been called with the same arguments before. If so, it returns the value it had calculated the first time it was called.5 If it hasn’t been called with the same arguments before, the function will instead call the function that was passed in to memo, and then store the result of that inside the table. This way, if the memoized function is called with the same arguments a second time, it can just look up the result in the table.

Next, for defmemo itself, we need to generate code that takes the body as a lambda expression, passes that lambda function through memo, and uses that as the implementation of the function. One way to set the implementation of a function to be a lambda function is to use setf with symbol-function.6 For example, here is how you could set the implementation of square to be a lambda function that squares its argument:

(setf (symbol-function 'square) (lambda (x) (* x x)))

(square 5) => 25

Based on the paragraph above, here is the code for defmemo:

(defmacro defmemo (name args &body body)
 `(setf (symbol-function ',name) 
        (memo (lambda ,args ,@body))))

Now instead of defining a function with defun, we can define it with defmemo and it will automatically be memoized! Defmemo is a great example of how you can define your own ways to define functions. Many libraries provide similar features in which you use the same syntax as defun, only with a bit of magic thrown in.