Programming in APL, for me at least, was like entering into a secondary zone after you were in the zone. The first step is to be in the "I am now focused on programming" zone. Then there's the "I am now in my problem space" zone. This is exactly how it works with APL.

I used the language extensively for probably a decade and nothing has ever approached it in this regard. Instead we are mired in the innards of the machine, micromanaging absolutely everything with incredible verbosity and granularity.

I really feel that for programming/computing to really evolve to another level we need to start loosing some of the links to the ancient world of programming. There's little difference between what you had to do with a Fortran program and what you do with some of the modern languages in common use. That's not he kind of progress that is going to make a dent.

This is one area where Haskell really shines. If you want the machine to be able to do what you want without micromanaging how, than you need a way to formally specify what you mean in an unambiguous and verifiable way. Yet it also needs to be flexible enough to cross domain boundaries (pure code, IO, DSLs, etc).

Category theory has been doing exactly that in the math world for decades, and taking advantage of that in the programming world seems like a clear way forward.

The current state of the industry seems like team of medieval masons (programmers) struggling to build a cathedral with no knowledge of physics beyond anecdotes that have been passed down the generations (design patterns), while a crowd of peasants watch from all angles to see if the whole thing will fall down (unit tests).

Sure, you might be able to build something that way, but it's not exactly science, is it?

Gimme a break.

A better analogy would be being mad that the Tesla can't drive on the interstate.

Don't confuse local maxima for maxima. We need people exploring other slopes for the chance of an apex, or at least some higher local maxima.

It's mostly good for being able to express mathematical formulas with very little translation from the math world - "executable proofs," I think the quote is - and having matrices of arbitrary dimension as first-class values is unusual if not unique. But for any practical purpose it's to Haskell what Haskell is to Java.

Can you elaborate on this? As I understand, the core strengths of APL are succinct notation, built-in verbs which operate on vectors/matrices, and a requirement to program in a point-free style. All of this can be done in Haskell.

A Haskell programmer unfamiliar with APL looks at an APL program and...

Of course, understanding the individual symbols is a different matter, but hardly requiring a conceptual leap.

And says "what's the big deal?". That's exactly the question, what is the big deal. APL isn't scary, I'm not shouting "I can't make sense of this", I am asking "how is this better than haskell in the same way haskell is better than java?".

Your question is fine, but not what he meant by the analogy.

Not that I dislike the idea -- on the contrary, I'm inclined to conclude from my excitement over this and Haskell that I dislike success...

On a related note, if one plans to sell the Language of The Future Of Programming, I swear this thing will know the same fate as Planner, NLS, Sketchpad, Prolog, Smalltalk and whatnot if it cannot help me with the problems I have to solve just tomorrow.

Now, I didn't learn APL from a tutorial, I learned it (in 1976) from a book. This book: http://www.jsoftware.com/papers/APL.htm from 1962.

If my memory hasn't been completely corrupted by background radiation, I've seen papers as early as the mid 1950s about this notation.

APL started out as a notation for expressing computation (this is not precise but good enough). As far as I'm concerned it's sitting at a level of abstraction higher than Haskell (arguably like a library overtop Haskell).

Now, in the theme of this thread, APL was able to achieve all of this given the constraints at the time.

The MCM/70 was a microprocessor based laptop computer that shipped in 1974 (demonstrated in 1972, some prototypes delivered to customers in 1973) and ran APL using an 80 kHz (that kilo) 8008 (with a whole 8 bytes of stack) with 2 kBytes (that's kilo) RAM or maxed out at 8 kB (again, that's kilo) of RAM. This is a small slow machine that still ran APL (and nothing else). IEEE Annals of Computer History has this computer as the earliest commercial, non-kit personal computer (IEEE Annals of the History of Computing, 2003: pg. 62-75). And, I say again, it ran APL exclusively.

Control Data dominated the super computer market in the 70s. The CDC 7600 (designed by Cray himself, 36.4 MHz with 65 kWord (a word was some multiple of 12 bits, probably 60 bits but I'm fuzzy on that) and about 36 MFLOPS according to wikipedia) was normally programmed in FORTRAN. In fact, this would be a classic machine to run FORTRAN. However, the APL implementation available was often able to outperform it, almost always when coded by an engineer (and I mean like civil, mechanical, industrial, etc engineer, not a software engineer) rather than someone specialising in writing fast software.

I wish everyone would think about what these people accomplished given those constraints. And think about this world and think again about Bret Victor's talk.

Were those destroyed tutorials published books?

EDIT: I just opened the drop down on the paper covered versions. Prices between $34.13 and $1806.23!!! Is that real?!? Wow, I had five or six copies of something that seems to be incredibly valuable. Too late for an insurance claim on that basement flood.

http://www.jdl.ac.cn/turing/pdf/p444-iverson.pdf

Share a thought or two with the peons who won't/can't travel :)

I guess one thing I will say is that our definition of programming is all over the place right now and that in order for us to get anywhere we need to scale it back to something that simplifies what it means to program. We're bogged down in so much incidental complexity that the definitions I hear from people are convoluted messes that have literally nothing to do with solving problems. That's a bad sign.

My thesis is that given the right definition all of the sudden things magically "just work" and you can use it to start cleaning up the mess. Without giving too much away I'll say that it has to do with focusing on data. :)

That's what inspired me to work on my [nameless graph language](http://nickretallack.com/visual_language/#/ace0c51e4ee3f9d74...). I thought it would be simpler to express a program by connecting information sinks to information sources, instead of ordering things procedurally. By using a graph, I could create richer expressions than I could in text, which allowed me to remove temporary variables entirely. By making names irrelevant, using UUIDs instead, I no longer had to think about shadowing or namespacing.

Also, by avoiding text and names, I avoid many arguments about "coding style", which I find extremely stupid.

I find that people often argue about programming methodologies that are largely equivalent and interchangeable. For example, for every Object Oriented program, there is an equivalent non-object-oriented program that uses conditional logic in place of inheritance. For every curried program, there is an equivalent un-curried program that explicitly names its function arguments. In fact, it wouldn't even be that hard to write a program to convert from one to the other.

I'm pretty excited about the array of parallel processors in the presentation though. If we had that, with package-on-package memory for each one, message passing would be the obvious way to do everything. Not sure how to apply this to my own language yet, but I'll think of something.

Max/MSP, Pure Data, vvvv, meemoo, Quartz Composer, Touch Designer, LabView, Grasshopper, WebAudioToy, just to name a few.

I'm used to JavaScript, so that's what I based my language on. It's really a traditional programming language in disguise, kinda like JavaScript with some Haskell influence. It's nothing like a dataflow language. On that front, perhaps those languages are a lot more avante-guarde than mine.

Chuck Moore, the inventor of Forth, is working on these processors.

http://www.greenarraychips.com/home/products/index.html

It hasn't been an easy road.

http://colorforth.com/blog.htm

I've been trying to do something similar with a pet language :) Human names should never touch the compiler, they are annotations on a different layer.

But writing an editor for such a programming environment with better UX and scalability than a modern text-based editor is... an engineering challenge.

It's not perfect, and making lambdas is still a little awkward because I haven't made them resizable. Also, eventually I'd like the computer to automatically arrange and scale the nodes for you, for maximum readability. But I think it's pretty fun to use. It'd probably be even more fun on an iPad.

I'd love to make my IDE as fun to use as DragonBox

It would be good if, while clicking and dragging a new connection line that will replace an old one, the latter's line is dimmed to indicate that it will disappear. Also, those blue nodes need a distinguishing selection color.

It sounds like you're aiming more toward a fun tablet-usable interface, but:

Have you thought about what it would take to write large programs in such an editor? For small fun programs a graph visualization is cool, but larger programs will tend toward a nested indented structure (like existing text) for the sake of visual bandwidth, readability of mathematical expressions, control flow, etc.

Use the arrow keys to move the box around. I suppose that's still a bit primitive, but I'll make some more involved programs once I fix up the scoping model a bit.

When I first started on this project, I thought at some point I would need to make a "zoom out" feature, because you might end up making a lot of nodes in one function. However, I have never needed this. As soon as you have too much stuff going on, you can just box-select some things and hit the "Join" button to get a new function. The restricted workspace actually forces you to abstract things more, and the lack of syntax allows you to reduce repetition more than would be practical in a textual language.

For example, in textual languages, reducing repetition often requires you to introduce intermediate variables, which could actually make the program's text longer, so people will avoid doing it. However, in my language you get intermediate variables by connecting two sinks to the same source. The addition in program length hardly noticeable.

The closest things to my language that I have seen are Kismet and UScript. Mine is different though because it is lazily evaluated and uses recursion as the only method of looping.

Some other things that look superficially similar such as Quartz Composer, ThreeNode, PureData, etc. are actually totally different animals. They are more like circuit boards, and my language is a lot more like JavaScript.

I don't think it is possible to make a program without conditional branches.

Somebody posted a link below about "Data Driven" design in C++. In it was an example of a pattern where each object has a "dirty" flag, which determines whether it needs processing, but they found that failing branch prediction here took more cycles than simply removing the branch.

My thought was, instead, what if you created two versions of that method -- one to represent when the dirty flag is true, and another to represent when the dirty flag is false -- and then instead of toggling the dirty flag, you could change the jump address for that method to point to the version it should use. If this toggle happens long enough before the the processor calls that method, you would remove any possibility of branch prediction failure =].

I have no idea if this is practical or not, but it is amusing to consider programs that modify jump targets instead of using traditional conditional branches.

Read more: http://en.wikipedia.org/wiki/Branch_predication EDIT: Also: http://en.wikipedia.org/wiki/Branch_predictor

I think we more commonly use the latter, which tries to guess which way the code will branch and load the appropriate jump target. It's actually typically very successful in modern processors.

(PS angular-js has done all that dirty flag checking if you like that approach)

In the same way that HN frowns upon stealth startups, shouldn't we frown upon 'stealth theories'? If your thoughts are novel and deep enough, revealing something about them will only increase interest in your future talks, since you are definitionally the foremost thinker in your unique worldview. If the idea fails scrutiny in some way, you should want to hear about it now so you can strengthen your position.

What's the downside, outside of using mystery to create artificial hype?

I think, the differences between reading and writing code are as big as sending and receiving packets. It's difficult to write code that extrapolates the base information in your head driving the decisions. Not only that, but you also have to juggle logic puzzles as you're doing it. And on the other side, you have to learn new domain languages (or type hierarchies), as well as what the program is supposed to do in the first place.

I think the idea of interacting with code as you build it is great, but how can we do that AND fix the information gap at the same time?

I agree.

For example, people do seem to assume that programming must involve, in some way, coding. Do we really need to code in some programming-language to be programming?

Changing security settings, for example, in a browser lead to quite different behaviors of the program. Isn't the user of the browser programming because they change the behavior of the program?

And this leads to....

> with focusing on data

If we focus on data, and hopefully better abstractions on how to manipulate that data, then wouldn't any user able to alter a program because they can adjust "settings" at almost any point within the program: in real time.

Wouldn't this then enable a lot more people to become programmers?

Anyway, just some thoughts.

A program is the result of the automation of some process (system) that people have thought up (even things that couldn't exist before computers). Programming is the act of taking that process (system) and describing it in a computing device of some kind.

Programming currently requires some kind of mapping from the "real world" to the "computer world". The current mapping is done primarily with source code. So, it currently seems that people who are good at programming are good at mapping from the "real world" into the "computer world" via coding.

You seem to be making the point that some people are just good at programming because they can do things like "re-discover the bubble sort algorithm" or understand CAP theorem. These are very domain specific problems.

For people who are able to "re-discover inventory control management" they would do a great job of automating it (programming) if they had an easier way to map that process (system) to a computing device.

The ultimate goal (other than maybe AI) is a 1-to-1 mapping between a "real world" process (system) and a computing device that automates it.

I'm curious what you mean by data though. Is it data in the "big data" sense? What I mean is, are we talking about gathering a lot of data on coding? My approach is based on that, anyway: lots of data on code with a number of different analyzers (static and dynamic) that allows for extraction of common idioms and constraints, while allowing for the system to more easily help the user.

Of course, there's no magic and a lot of times I reach dead-ends, and while I'm eager to have enough to show the world, progress has been kinda slow lately.

Looking forward for your talk, be sure to link here on HN.

We had some great discussions at LIXD a couple of weeks ago, wish you could have been there. Everyone seems to be reinventing programming these days. We are definitely in competition to some extent. The race is on.

That's exactly what I'm up to :)

I'll (hopefully) be looking forward to a vid of it on infoq at some point. :)

Either way, looking forward too it!