Monthly Archives: July 2016

Jovian Prayer

Big slow storms of Jupiter, help sooth us.
Sooth us with your patient weather, ochre,
gamboge, carmine, grey, swirling storms, giant.
And auroras, lightning, huge, cathartic.Screen Shot 2016-07-10 at 10.46.37 AM

Let us be like Galileo’s nameless
daughter, who threw herself into your heart
wrapped in curiosity, down, down, down,
swallowed by knowledge, by your huge brown storms.

The Fetishist

Slow mottled gray skies, the empty plains
somewhere in the blown out corridor from
Houston to Galveston. Highway and plane
noise, far enough for privacy but frisson-
near enough for wanderers to run, run
the risk of observation, forced sight:
so much more than the dead camera, glum
in its facile adsorption of light.
An old abandoned pool languishing right
behind an encroached upon foundation,
obscenely, a chimney still stands, a blight
within a blight within a blight within station-
ary air. He mugs against the gray sky
and falls into shit for the camera’s eye.


On Inform 7, Natural Language Programming and the Principle of Least Surprise

I’ve been pecking away at Inform 7 lately on account of its recently acquired Gnome front end. For those not in the know, Inform (and Inform 7) is a text adventure authoring language. I’ve always been interested in game programming but never had the time (or more likely the persistence of mind) to develop one of any sophistication myself. Usually in these cases one lowers the bar, and as far as interactive media goes, you can’t get much lower, complexity wise, than text adventures.

Writing a game in Inform amounts to describing the world and it’s rules in terms of a programming language provided by Inform. The system then collects the rules and descriptions and creates a game out of them. Time was, programming in Inform used to look like:

Constant Story "Hello World";
Constant Headline "^An Interactive Example^";
Include "Parser";
Include "VerbLib";
[ Initialise;
  location = Living_Room;
  "Hello World"; ];
Object Kitchen "Kitchen";
Object Front_Door "Front Door";
Object Living_Room "Living Room"
      description "A comfortably furnished living room.",
      n_to Kitchen,
      s_to Front_Door,
  has light;

Which is recognizably a programming language, if a bit strange and domain specific. These days, writing Inform looks like this: (from my little project):

"Frustrate" by "Vincent Toups"
Ticks is a number which varies.
Ticks is zero.
When play begins:  
Now ticks is 1.

The Observation Room is a room. "The observation room cold and
surreal. Stars dot the floor underneath thick, leaded glass, cutting
across it with a barely perceptible tilt. This room seems to have been
adapted for storage, and is filled with all sorts of sub-stellar
detritus, sharp in the chill and out of place against the slowly
rotating sky. Even in the cold, the place smells of dust, old wood
finish, and mildew. [If ticks is less than two] As the sky cuts its
way across the milky way, the whole room seems to tilt.  You feel
dizzy.[else if ticks is less than four]The plane of the galaxy is
sinking out of range and the portal is filling with the void of
space. It feels like drowning.[else if ticks is greater than 7]The
galactic plane is filling the floor with a powdering of
stars.[else]The observation floor looks out across the void of space.
You avert your eyes from the floor.[end if]"

Every turn: Now ticks is ticks plus one.
Every turn: if ticks is 10:
decrease ticks by 10.

As you can see, the new Inform adopts a “natural language” approach to programming. As the Inform 7 website puts it

[The] Source language [is] modelled closely on a subset of English, and usually readable as such.

Also reproduced in the Inform 7 manual is the following quote from luminary Donald Knuth:

Programming is best regarded as the process of creating works of literature, which are meant to be read… so we ought to address them to people, not to machines. (Donald Knuth, “Literate Programming”, 1981)

Which better than anything else illustrates the desired goal of the new system: Humans are not machines! Machines should accommodate our modes of expression rather than forcing us to accommodate theirs! If it wasn’t for the unnaturalness of programming languages, the logic goes, many more people would program. The creation of interactive fiction means to be inclusive, so why not teach the machine to understand natural language?

This is a laudable goal. I really think the future is going to have a lot more programmers in it, and a primary task of language architects is to design programming languages which “regular” people find intuitive and useful. For successes in that arena see Python, or Smalltalk or even Basic. Perhaps these languages are not the pinnacle of intuitive programming environments but whatever that ultimate language is, I doubt seriously it will look much like Inform 7.

This is unfortunate, because reading Inform 7 is very pleasant, and the language is even charming from time to time. Unfortunately, it’s very difficult to program in1, and I say that as something of a programming language aficionado. It’s true that creating the basic skeleton of a text adventure is very easy, but even slightly non-trivial extensions to the language are difficult to intuitively get right. For instance, the game I am working on takes place on a gigantic, hollowed out natural satellite, spinning to provide artificial gravity. The game begins in a sort of observation bubble, where the floor is transparent and the stars are visible outside. Sometimes this observation window should be pointing into the plane of the Milky Way, but other times it should be pointing towards the void of space because the station’s axis of rotation is parallel to the plane of the galaxy. The description of the room should reflect these different possibilities.

Inform 7 operates on a turn based basis, so it seems like it should be simple enough to create this sort of time dependent behavior by keeping track of time but it was frustrating to figure out how to “tell” the Inform compiler what I wanted.

First I tried joint conditionals:

  When the player is in the Observation Room and
the turn is even, say: "The stars fill the floor."

But this resulted in an error message. Maybe the system doesn’t know about “evenness” so I tried:

  When the player is in the Observation Room and
the turn is greater than 3, say "The stars fill the floor."

(Figuring I could add more complex logic later).

Eventually I figured out the right syntax, which involved creating a variable and having a rule set its value each turn and a separate rule reset the value with the periodicity of the rotation of the ship, but the process was very frustrating. In Python the whole game might look, with the proper abstractions, like:

while not game.over():
    if (player.position == 'The Observation Room' and
         game.turn() % 10):
        print "The stars fill the floor."

Which is not perhaps as “englishy” as the final working Inform code (posted near the beginning of this article) but is much more concise and obvious.

But that isn’t the reason the Python version is less frustrating to write. The reason is the Principle of Least Surprise, which states, roughly, that once you know the system, the least surprising way of doing things will work. The problem with Inform 7 is that “the system” appears to the observer to be “written English (perhaps more carefully constructed that usual)”. This produces in the coder a whole slew of assumptions about what sorts of statements will do what kind of things and as a consequence, you try a lot of things which, according to your mental model, inexplicably don’t work.

It took me an hour to figure out how to make what amounts to a special kind of clock and I had the benefit of knowing that underneath all that “natural English” was a (more or less) regular old (prolog flavored) programming environment. I can’t imagine the frustration a non-programmer would feel when they first decided to do something not directly supported or explained in the standard library or documentation.

That isn’t the only problem, either. Natural english is a domain specific language for communicating between intelligent things. It assumes that the recepient of the stream of tokens can easily resolve ambiguities, invert accidental negatives (pay attention, people do this all the time in speech) and tell the difference between important information and information it’s acceptable to leave ambiguous. Not only are computers presently incapable of this level of deduction/induction, but generally speaking we don’t want that behavior anyway: we are programming to get a computer to perform a very narrowly defined set of behaviors. The implication that Inform 7 will “understand you” in this context is doubly frustrating. And you don’t want it to “understand,” you want it to do exactly.

A lot of this could be ameliorated by a good piece of reference documentation, spelling out in exact detail the programmatic environment’s behavior. Unfortunately, the bundled documentation is a big tutorial which does a poor job of delineated between constructs in the language and elements of it. It all seems somewhat magical in the tutorial, in other words, and the intrepid reader, wishing to generalize on the rules of the system, is often confounded.

Nevertheless, I will probably keep using it. The environment is clean and pleasant, and the language, when you begin to feel out the classical language under the hood, is ok. And you can’t beat the built in features for text based games. I doubt that Inform 7, though, will seriously take off. Too many undeliverable promises.

1 This may make it the only “Read Only” programming language I can think of.

A Critique of The Programming Language J

I’ve spent around a year now fiddling with and eventually doing real
data analytic work in the The Programming Language J. J is one of
those languages which produces a special enthusiasm from its users and
in this way it is similar to other unusual programming languages like
Forth or Lisp. My peculiar interest in the language was due to no
longer having access to a Matlab license, wanting an array oriented
language to do analysis in, and an attraction to brevity and the point
free programming style, two aspects of programming which J emphasizes.

Sorry, Ken.

Sorry, Ken.

I’ve been moderately happy with it, but after about a year of light
work in the language and then a month of work-in-earnest (writing
interfaces to gnuplot and hive and doing Bayesian inference and
spectral clustering) I now feel I am in a good position to offer a
friendly critique of the language.

First, The Good

J is terse to nearly the point of obscurity. While terseness is not a
particularly valuable property in a general purpose programming
language (that is, one meant for Software Engineering), there is a
case to be made for it in a data analytical language. Much of my work
involves interactive exploration of the structure of data and for that sort
of workflow, being able to quickly try a few different ways of
chopping, slicing or reducing some big pile of data is pretty
handy. That you can also just copy and paste these snippets into some
analysis pipeline in a file somewhere is also nice. In other words,
terseness allows an agile sort of development style.

Much of this terseness is enabled by built in support for tacit
programming. What this means is that certain expressions in J are
interpreted at function level. That is, they denote, given a set of
verbs in a particular arrangement, a new verb, without ever explicitly
mentioning values.

For example, we might want a function which adds up all the maximum
values selected from the rows of an array. In J:


J takes considerable experience to read, particularly in Tacit
style. The above denotes, from RIGHT to LEFT: for each row ("1)
reduce (/) that row using the maximum operation >. and then (@:)
reduce (/) the result using addition (+). In english, this means:
find the max of each row and sum the results.

Note that the meaning of this expression is itself a verb, that is
something which operates on data. We may capture that meaning:

sumMax =: +/@:(>./"1)

Or use it directly:

+/@:(>./"1) ? (10 10 $ 10)

Tacit programming is enabled by a few syntactic rules (the so-called
hooks and forks) and by a bunch of function level operators called
adverbs and conjuctions. (For instance, @: is a conjunction rougly
denoting function composition while the expression +/ % # is a fork,
denoting the average operation. The forkness is that it is three
expressions denoting verbs separated by spaces.

The details obscure the value: its nice to program at function level
and it is nice to have a terse denotation of common operations.

J has one other really nice trick up its sleeve called verb
. Rank itself is not an unusual idea in data analytic languages:
it just refers to the length of the shape of the matrix; that is, its

We might want to say a bit about J’s basic evaluation strategy before
explaining rank, since it makes the origin of the idea more clear. All
verbs in J take one or two arguments on the left and the right. Single
argument verbs are called monads, two argument verbs are called dyads.
Verbs can be either monadic or dyadic in which case we call the
invocation itself monadic or dyadic. Most of J’s built-in operators
are both monadic and dyadic, and often the two meanings are unrelated.

NB. monadic and dyadic invocations of <
4 < 3 NB. evaluates to 0
<3 NB. evalutes to 3, but in a box.

Give that the arguments (usually called x and y respectively) are
often matrices it is natural to think of a verb as some sort of matrix
operator, in which case it has, like any matrix operation, an expected
dimensionality on its two sides. This is sort of what verb rank is
like in J: the verb itself carries along some information about how
its logic operates on its operands. For instance, the built-in verb
-: (called match) compares two things structurally. Naturally, it
applies to its operands as a whole. But we might want to compare two
lists of objects via match, resulting in a list of results. We can
do that by modifying the rank of -:

x -:”(1 1) y

The expression -:”(1 1) denotes a version of match which applies to
the elements of x and y, each treated as a list. Rank in J is roughly
analogous the the use of repmat, permute and reshape in Matlab: we can
use rank annotations to quickly describe how verbs operate on their
operands in hopes of pushing looping down into the C engine, where
it can be executed quickly.

To recap: array orientation, terseness, tacit programming and rank are
the really nice parts of the language.

The Bad and the Ugly

As a programming environment J can be productive and efficient, but it
is not without flaws. Most of these have to do with irregularities in
the syntax and semantics which make the language confusing without
offering additional power. These unusual design choices are
particularly apparent when J is compared to more modern programming

Fixed Verb Arities

As indicated above, J verbs, the nearest cousin to functions or
procedures from other programming languages, have arity 1 or
arity 2. A single symbol may denote expressions of both arity, in
which case context determines which function body is executed.

There are two issues here, at least. The first is that we often want
functions of more than two arguments. In J the approach is to pass
boxed arrays to the verb. There is some syntactic sugar to support
this strategy:

multiArgVerb =: monad define
‘arg1 arg2 arg3’ =. y
NB. do stuff

If a string appears as the left operand of the =. operator, then
simple destructuring occurs. Boxed items are unboxed by this
operation, so we typically see invocations like:

multiArgVerb('a string';10;'another string')

But note that the expression on the right (starting with the open
parentheses) just denotes a boxed array.

This solution is fine, but it does short-circuit J’s notion of verb
rank: we may specify the the rank with which the function operates on
its left or right operand as a whole, but not on the individual
“arguments” of a boxed array. But nothing about the concept of rank
demands that it be restricted to one or two argument functions: rank
entirely relates to how arguments are extracted from array valued
primitive arguments and dealt to the verb body. This idea can be
generalized to functions of arbitrary argument count.

Apart from this, there is the minor gripe that denoting such single
use boxed arrays with ; feels clumsy. Call that the Lisper’s bias:
the best separator is the space character.1

A second, related problem is that you can’t have a
zero argument function either. This isn’t the only language where
this happens (Standard ML and OCaml also have this tradition, though I
think it is weird there too). The problem in J is that it would feel
natural to have such functions and to be able to mention them.

Consider the following definitions:

o1 =: 1&-
o2 =: -&1

(o1 (0 1 2 3 4)); (o2 (0 1 2 3 4))
│1 0 _1 _2 _3│_1 0 1 2 3│

So far so good. Apparently using the & conjunction (called “bond”)
we can partially apply a two-argument verb on either the left or the
right. It is natural to ask what would happen if we bonded twice.


Ok, so it produces a verb.

 3 3 $ ''
  ;((o1&1 (0 1 2 3 4))
  ; (o2&1 (0 1 2 3 4))
  ; (1&o1 (0 1 2 3 4))
  ; (1&o2 (0 1 2 3 4)))

│     │o1          │o2          │
│right│1 0 1 0 1   │1 0 _1 _2 _3│
│left │1 0 _1 _2 _3│_1 0 1 2 3  │

I would describe these results as goofy, if not entirely impossible to
understand (though I challenge the reader to do so). However, none of
them really seem right, in my opinion.

I would argue that one of two possibilities would make some sense.

  1. (1&-)&1 -> 0 (eg, 1-1)
  2. (1&-)&1 -> 0″_ (that is, the constant function returning 0)

That many of these combinations evaluate to o1 or o2 is doubly
confusing because it ignores a value AND because we can denote
constant functions (via the rank conjunction), as in the expression


What this is all about is that J doesn’t handle the idea of a
function very well. Instead of having a single, unified abstraction
representing operations on things, it has a variety of different ideas
that are function-like (verbs, conjuctions, adverbs, hooks, forks,
gerunds) which in a way puts it ahead of a lot of old-timey languages
like Java 7 without first order functions, but ultimately this
handful of disparate techniques fails to acheive the conceptual unity
of first order functions with lexical scope.

Furthermore, I suggest that nothing whatsoever would be lost (except
J‘s interesting historical development) by collapsing these ideas
into the more typical idea of closure capturing functions.

Other Warts

Weird Block Syntax

Getting top-level2 semantics right is hard in any
language. Scheme is famously ambiguous on the subject, but at
least for most practical purposes it is comprehensible. Top-level has
the same syntax and semantics as any other body of code in scheme
(with some restrictions about where define can be evaluated) but in
J neither is the same.

We may write block strings in J like so:

blockString =: 0 : 0 
Everything in here is a block string.       

When the evaluator reads 0:0 it switches to sucking up characters
into a string until it encounters a line with a ) as its first
character. The verb 0:3 does the same except the resulting string is
turned into a verb.

plus =: 3 : 0

However, we can’t nest this syntax, so we can’t define non-tacit
functions inside non-tacit functions. That is, this is illegal:

plus =: 3 : 0
  plusHelper =. 3 : 0
  x plusHelper y

This forces to the programmer to do a lot of lambda lifting
manually, which also forces them to bump into the restrictions on
function arity and their poor interaction with rank behavior, for if
we wish to capture parts of the private environment, we are forced to
pass those parts of the environment in as an argument, forcing us to
give up rank behavior or forcing us to jump up a level to verb


Of course, you can define local functions if you do it tacitly:

plus =: 3 : 0
    plusHelper =. +
    x plusHelper y   

But, even if you are defining a conjunction or an adverb, whence you
are able to “return” a verb, you can’t capture any local functions –
they disappear as soon as execution leaves the conjunction or adverb

That is because J is dynamically scoped, so any capture has to be
handled manually, using things like adverbs, conjunctions, or the good
old fashioned fix f., which inserts values from the current scope
directly into the representation of a function. Essentially all modern
languages use lexical scope, which is basically a rule which says: the
value of a variable is exactly what it looks like from reading the
program. Dynamic scope says: the valuable of the variable is whatever
its most recent binding is.


The straight dope, so to speak, is that J is great for a lot of
reasons (terseness, rank) but also a lot of irregular language
features (adverbs, conjunctions, hooks, forks, etc) which could be
folded all down into regular old functions without harming the
benefits of the language, and simplifying it enormously.

If you don’t believe that regular old first order functions with
lexical scope can get us where we need to go, check out my
tacit-programming libraries in R and Javascript. I
even wrote a complete, if ridiculously slow implementation of J‘s
rank feature, literate-style, here.


1 It bears noting that ; in an expression like (a;b;c)
is not a syntactic element, but a semantic one. That is, it is the
verb called “link” which has the effect of linking its arguments into
a boxed list. It is evaluated like this:


(a;b;c) is nice looking but a little strange: In an expression
(x;y) the effect depends on y is boxed already or not: x is always boxed regardless, but y is boxed only if it wasn’t boxed before.

2 Top level? Top-level is the context where everything
“happens,” if anything happens at all. Tricky things about top-level
are like: can functions refer to functions which are not yet defined,
if you read a program from top to bottom? What about values? Can you
redefine functions, and if so, how do the semantics work? Do functions
which call the redefined function change their behavior, or do they
continue to refer to the old version? What if the calling interface
changes? Can you check types if you imagine that functions might be
redefined at any time? If your language has classes, what about
instances created before a change in the class definition. Believe or
not, Common Lisp tries to let you do this – and its confusing!

On the opposite end of the spectrum are really static languages like
Haskell, wherein type enforcement and purity ensure that the top-level
is only meaningful as a monolith, for the most part.