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SKILL for the Skilled: The Partial Predicate Problem

Comments(2)Filed under: SKILL, Team SKILL, programming, LISP, SKILL++, IC615, Jim Newton, SKILL for the Skilled, CPS, continuation passing, partial predicateThe partial predicate problem describes the type of problem encountered when a function needs to usually return a computed value, but also may need to return a special value indicating that the computation failed. Specifically, the problem arises if the caller cannot distinguish this special value from a successfully calculated value. In this posting of SKILL for the Skilled, we look at several ways to attach this problem in SKILL.

Approach 1: Returning nil to indicate failure

A very common way a SKILL function indicates to its caller that it failed to do what was requested is to return nil. For example, the SKILL function nthelem returns the Nth element of a given list, given an integer N. If the list has less than N elements, it returns nil. For example (nthelem 2 '(10 20 30)) returns 20, but (nthelem 4 '(10 20 30)) returns nil.

A limitation of this approach is that (nthelem 2 '(t nil t)) also returns nil, because nil is the second element. The caller can only trust nil to be the failure case if he knows that nil is not an element of the list.

Here is an implementation of a find function which returns the first element of a given list which matches a given predicate. Note that this example (and most of the examples in this article) only work in Scheme/Skill++ mode.

(defun find_A (predicate data)
  (car (exists x data
         (predicate x))))

Here are some examples of how it works.

(find_A oddp '(2 4 5 6 7 9))
==> 5

(find_A stringp '(this is 1 "list" of stuff))
==> "list"

(find_A numberp '(this is a list of symbols))
==> nil

(find_A listp '(t t t nil t t))
==> nil

Notice that the find_A function returns nil in two cases:

  • if there is no element in the given list which matches the predicate
  • if nil is explicitly in the given list and matches the predicate
Thus if find_A returns nil you don't know whether it found something or not.

Approach 2: Returning a given default value on failure

The following implementation of find_B attempts to settle the ambiguity by allowing the caller to specify the return value on the so-called failure case.
(defun find_B (predicate data @key default)
  (let ((tail (exists x data
                (predicate x))))
    (if tail
        (car tail)

(find_B stringp '(this is 1 "list" of stuff) ?default 'notfound)
==> "list"

(find_B listp '(t t t nil t t) ?default 'notfound)
==> nil

(find_B numberp '(this is a list of symbols) ?default 'notfound)
==> notfound

A disadvantage of this case is that the caller might find it clumsy at the call-site to provide a value which the given function call would otherwise never return.

Approach 3: Wrapping the return value on success

Another common way is to return a wrapped value. I.e., don't return the value found/computed, but rather return a list whose first element is that computed value. The SKILL member function does just this. (member 5 '(1 2 3 4)) returns nil because the given list does not contain 5; whereas (member 3 '(1 2 3 4) returns a list (3 4). Thus the only time member returns nil is when it didn't find the value being sought.

Another function which uses this approach is errset, which returns nil if the given form to evaluated triggered an error. Otherwise, errset returns a singleton list whose first (and only) element is the value calculated. Thus (errset 6/4) returns (3), while (errset 6/0) returns nil.

An obvious advantage of this wrapping approach is that the failure condition can always be distinguished from the success case. A disadvantage is that the caller who wants to use the calculated value must unwrap the value with an additional call to car, probably after testing whether the value is nil.

Here is an implementation of find_C which wraps its return value. It only returns nil if no element of the list matches the predicate. But the caller must call car to unwrap the value.

(defun find_C (predicate data)
  (let ((tail (exists x data
                (predicate x))))
    (when tail
      (ncons (car tail)))))

(find_C stringp '(this is 1 "list" of stuff) ?default 'notfound)
==> ("list")

(find_C listp '(t t t nil t t) ?default 'notfound)
==> (nil)

(find_C numberp '(this is a list of symbols) ?default 'notfound)
==> nil

Another disadvantage of this approach is that find_C always allocates memory if it successfully finds what its looking for.

Approach 4: Continuation passing

Still another way to solve this problem in SKILL++ is by passing a continuation. This involves organizing your code a bit differently, but in the end allows a lot of flexibility. The idea is to pass an extra argument which is itself a function to call with the computed value if successful.
(defun find_D (predicate data @key (if_found (lambda (x) x)))
  (let ((tail (exists x data
                (predicate x))))
    (when tail
      (if_found (car tail)))))
The find_D function searches the given list for an element matching the condition. If successful, calls the given function, if_found and returns the value it returns. Otherwise it omits calling the if_found and simply returns nil.

Continuation passing is a generalization

As you can see from the examples below, the function find_D is actually a generalization of find_A, find_B, and find_C.

These examples work like find_A.

(find_D stringp '(this is 1 "list" of stuff))
==> "list"

(find_D listp '(t t t nil t t))
==> nil

(find_D numberp '(this is a list of symbols))
==> nil
These examples work like find_B.
(find_D stringp '(this is 1 "list" of stuff) ?if_found (lambda (x) 'notfound))
==> "list"

(find_D listp '(t t t nil t t) ?if_found (lambda (x) 'notfound))
==> notfound

(find_D numberp '(this is a list of symbols) ?if_found (lambda (x) 'notfound))
==> notfound
These examples work like find_C.
(find_D stringp '(this is 1 "list" of stuff) ?if_found ncons)
==> ("list")

(find_D listp '(t t t nil t t) ?if_found ncons)
==> (nil)

(find_D numberp '(this is a list of symbols) ?if_found ncons)
==> nil

An initial reaction of this type of coding might be that it looks more complicated. But in fact, it is often less complicated when you actually try to use it. Why is this? It is because the code at the call-site usually needs to (1) do something with the calculated value. In addition, there must be program logic, to (2) test whether the value corresponds to the success case or the failure case.

The way find_D is intended to be used, the code for case (1) goes inside the function being passed as the ?if_found argument, and the code for case (2) is already inside the find_D implementation. This is shown in the following examples.

Example using continuation passing

Assume we have a function, is_metal_shape?, which figures out whether a given shape is on a metal layer, presumably by looking at the layer name of the shape and looking in the tech file to see whether that layer has "metal" function. Here is an example of how to use find_B and find_D to add such a shape to a particular db-group.


(let ((shape (find_B is_metal_shape? cv~>shapes
                 ?default 'notfound))
   (unless (shape == 'notfound)
     (dbAddObjectToGroup dbGroup shape)))

Notice that the call to find_D is actually simpler.


(find_D is_metal_shape? cv~>shapes
    ?if_found (lambda (shape)
                (dbAddObjectToGroup dbGroup shape)))

This approach has certain advantages over all the alternatives shown above. The most obvious advantage is that there is no ambiguity at the call-site. The caller does not have to tend with the failure condition. In fact it is the function find_D itself which knows whether the sought element was found and deals with it appropriately.

Handling the found and not-found cases separately

One might also write a version of function find_D with an additional if_not_found keyword argument to handle the other case that the call-site wants to do something different if such an element is not found--for example to trigger an error.
(defun find_E (predicate data @key 
                                (if_found (lambda (x) x))
                                (if_not_found (lambda (_x) nil)))
  (let ((tail (exists x data
                (predicate x))))
    (if tail
        (if_found (car tail))


In the above paragraphs, we saw several common ways of dealing with the so-called partial predicate problem in SKILL.
  • Return nil to indicate failure
  • Return a given default value to indicate failure
  • Wrap the return value
  • Pass a continuation to call on success.

In general continuation passing can indeed be very complicated, but there are certainly cases such as the example shown here, where the style is simple to use and eliminates complexity from your code with no added overhead.

See also

Jim Newton


By Haitham Gad on December 3, 2013
find_C can also be viewed as returning a monadic value (in Haskell terminology). I think it's the best approach for a statically-typed language that supports pattern matching. For a dynamically-typed language (like SKILL), I usually use approach 1 whenever I can i.e. when I know that nil cannot represent any success scenarios.

By Team SKILL on December 4, 2013
Hi Haitham, thanks for your comment.  Yes, I also think approach one is the most common. I've heard case 1 referred to also as nil-punning.

Kind regards


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