It didn't seem like too much of a hardship. In a previous Forth I'd built, I'd implemented do / loop using the return stack, but it was... ugly. The code to implement it was ugly, the code it generated was ugly (and large!), and I didn't find a lot of places where it was actually much nicer to use than explicit begin-based loops. I was able to implement an 8086 assembler and a Minesweeper game without bothering to build do / loop. I didn't really miss it, but I had a design percolating in the back of my mind that I wanted to try.

At some point I came across some writing that suggested that Forth had a “loop control stack”. Wouldn't it be nice if I could implement some kind of loop control stack that worked for all kinds of iteration?

The thing I built has blown me away with how flexible, composable, and useful it's turned out to be. It's way more powerful than I was expecting. And the code that leverages it is inevitably much simpler and easier to read.

The Stacks

I added two loop control stacks – what I call the i-stack, and the next-stack. The i-stack contains the current value(s) being iterated over, and is read from with the i and j words like normal. The next-stack is where the magic happens.

When iterating, the top value of the next-stack is a pointer to a small structure called an iterator. It's a very simple structure, only two cells. The first cell contains the execution token of a word that will either update the current values on the i-stack and return true, or remove its state from both stacks and return false. The second cell points to a cancellation function, that cleans up whatever state the iterator has kept on the two stacks without iterating further, and returns nothing.

Iterators

I built some simple helpers for creating iterators. It took a few tries to nail down this design, but I'm happy with it now. defiter creates a “blank” iterator, which, when called, pushes itself to the next-stack. :iter does the same thing but allows you to write some code that accepts parameters and prepares the loop stacks first. :next defines a new anonymous “next-word” and assigns it to the most-recently defined iterator. :cancel does the same thing, but for cancellation.

On its own, this is already quite nice. I've got a page or so of basically-trivial iterators. Here's one:

:iter times ( n -- ) >i ;
:next <i dup 1- >i finish? ;
:cancel idrop nextdrop ;

times keeps its state in the i-stack – it initializes itself by pushing the number of times to repeat onto it. When fetching the next value, it pops the current value off the i-stack, decrements it, and pushes it back, leaving the old value on the data stack. finish? is a simple helper word that peeks at the top of the stack and runs the current cancellation function if it's false, or in this case, if we've already hit 0. Since cleaning up after an iterator is often the same job whether you're exiting early or not, this word is very handy. Explicitly defining cancellation for this iterator isn't actually necessary in my current implementation, because idrop nextdrop is common enough that I use it as the default.

each / next

I can use these iteration words (within a compiled definition) like this:

5 times each i . next
( outputs: 4 3 2 1 0 )

All the common loop types are easy to build in this system, as well as some uncommon ones:

5 10 for each i . next ( outputs: 5 6 7 8 9 )
0 10 2 for+ each i . next ( outputs: 0 2 4 6 8 )
( pchars yields pointers to each byte in a zero-terminated string )
s" hello" pchars each i b@ emit next ( outputs: hello )

Generic cancellation, of course, allows us to trivially implement break; just cancel the iteration at the top of the stack, and then jump to the each loop exit point, after next. continue is even simpler, just jump back to the top of the loop.

5 times each i 3 < if break then i . next ( outputs: 4 3 )
5 times each i 2 % if continue then i . next ( outputs 4 2 0 )

Under the hood, each just calls the “next-word” of the iterator and jumps to the end of the loop if it returns 0 – conceptually identical to begin iterate while, with next meaning the same thing as repeat. This allows for iterators that return no values.

0 times each i . next ( outputs: )

Generators

That's nice, but it's not exactly setting the world on fire; it's a fair amount of work just to end up with a few different ways of writing “for” loops in practice, that Forth systems have had forever anyway. Is it really worth the cost of this abstraction?

Turns out, absolutely, yes, it is, because you can also build generators on it, and that blows things wide open.

First, a simple example:

: 5-2-8 (( 5 yield 2 yield 8 yield )) ;
5-2-8 each i . next ( outputs: 5 2 8 )

(( defines the start of the generator, and )) defines the end (and pushes it onto the next-stack). Any valid Forth code goes in between. yield takes the top of the stack, pushes it onto the i-stack, and then suspends the generator until the next iteration. How does this work? Essentially, yield takes the top of the return stack and pushes it onto the next-stack, then pushes an iterator that pops it off the next-stack and pushes it back onto the return stack. The details get a little messier in order to support some more advanced use cases, but that's the simple idea at the core of it.

OK, neat trick, we've built ourselves a nice little coroutine-like system. But wait! It gets better! When yield resumes, it immediately removes all of its state from the iteration stacks. This means that generators can safely interact with any iterator that might be “underneath” it. They can iterate over things and yield in the middle! They can yield different things based on those values! We've accidentally built an extremely powerful, totally generic map/filter capability!

: doubled (( each i i + map next )) ;
5 times doubled each i . next ( outputs: 8 6 4 2 0 )
: odd (( each i 2 % filter next )) ;
5 times odd each i . next ( outputs: 3 1 )

map and filter are more yield-like words – it turns out that there's a number of these that you might want to implement, with different logic for suspending, resuming, and cancelling. map saves the top of the i-stack onto the next-stack and replaces it with the input, restoring the original value after resuming (necessary since the iterator underneath might be using that value as its state). filter conditionally suspends based on the top of the data stack but otherwise doesn't touch the i-stack, leaving whatever iterator is running underneath to provide the value. Both of these words push iterators with special cancel logic that knows that there is another iterator underneath, and can cancel again recursively once they've cleaned themselves up.

Generator state

This design can almost be made to work for generators that have extra state, but it's awkward and incomplete. You must ensure the data stack is clean whenever you yield, so you're forced to manually shuffle data to and from the next stack. Consider a filter that only returns values that are divisible by a certain number:

: divisible-by ( n -- ) >next 
  (( <next each i over % 0 = swap >next filter <next next drop )) ;
5 divisible-by 21 times each i . next ( ouputs: 20 15 10 5 0 )

This works, but there's so much stack noise! And it breaks down if you need to cancel, because filter has no idea that there's extra stuff on the next-stack that it needs to clear. Ideally there would be some automatic way of keeping the state of the generator on the data stack while it's running, and push it safely away when we suspend. Could there be some way to write divisible-by like this?

: divisible-by ( n -- ) >arg (( each i over % 0 = filter next drop )) ;

In fact, this code works in my implementation. The scheme to make this happen is a little bit subtle, but it can be done efficiently with a minimum of bookkeeping noise in most cases. I define a variable, gen-arg-count, that starts at zero. >arg is an immediate word that compiles a call to >next and increments that variable. Then, any time I compile a yielding word, I append the value of gen-arg-count to the instruction stream – much like lit. When suspending, the yielding word reads that value out of the instruction stream and transfers that many values from the data stack to the next-stack. Then it moves the pointer to the instruction stream from the return stack to the next-stack, and finally pushes the yielding iterator. That iterator then pulls the instruction pointer back off the next-stack to determine how many values to move from the next-stack back onto the data stack, as well as where to resume the instruction stream. Cancellation similarly can read the arg-count byte to know how many extra values to drop from the next-stack.

Generators need to ensure the data stack is empty before exiting at )). At one point I considered having )) compile the appropriate number of drop calls automatically, but in the end I decided that it's reasonable and idiomatic to expect a generator to exit with a clean stack, like any other Forth word would.

With this extension, it's trivial to write all kinds of new iterators – we could even do away with the base iterator system entirely and just express everything as generators. There are lots nice one-line definitions of times:

( 1 ) : times ( n -- ) >arg (( begin dup while 1- dup yield repeat drop )) ;
( 2 ) : times ( n -- ) >next (( <next begin dup while 1- yield> repeat drop )) ;
( 3 ) : times ( n -- ) >arg (( -arg begin dup while 1- yield> repeat drop )) ;
( 4 ) ( suspend ) ' noop ( resume ) ' noop ( cancel ) ' idrop :yield iyield
: times ( n -- ) >i (( begin i while <i 1- >i iyield repeat idrop )) ;

Definition 1 doesn't use anything I haven't already explained. The state of the iterator is managed on the data stack, and automatically shuffled back and forth from the next-stack by yield.

Definition 2 adds a new word. yield> is a yielder that moves the yielded value from the i-stack back onto the data stack when it resumes, instead of dropping it. The state of the iterator starts on the next-stack but is moved to the i-stack once the iteration loop actually starts.

Definition 3 is virtually the same as 2, but demonstrates the ability to handle changes in the amount of state. -arg is an immediate word that generates no code, but decrements gen-arg-count so that you can express that you've consumed the argument and the next yield should preserve one less value on the data stack. (+arg is also defined, performing an increment, in case you generate more values on the stack than you started with.)

Definition 4 is built to keep all state on the i-stack from the beginning. Here we use :yield to define a new yielding word. I realized I hadn't built a yielder that left the i-stack alone when resuming, but would drop the value when cancelling, so I added one.

All of these options will correctly be cancelled if the code iterating over it calls break, with no special effort!

Final thoughts

With this scheme, generators always take up at least two spaces on the next-stack – one for the yielder's iterator, and one for the resume point. But if all iterators were defined as generators, and all yielding words had to be defined with :yield to ensure a uniform structure, we could just push the resume point. iterate and cancel could easily find the appropriate function pointer by looking next to the resume point for the address of the yielder and digging inside. I think this could be built in such a way that it would be basically as efficient as the existing scheme, at the cost of making the whole thing more complex to explain. It might be worth pursuing, because generators are so pleasant to read and write, and raw iterators are... less so. I basically never want to write a raw iterator besides the very basic ones that are built-in.

All the source for my Forth system is available online; the iteration system is defined in iter.jrt. There are some interesting examples of generators in embed.jrt, dialer.jrt and rick.jrt – some highlights:

• rle-decode – takes a pointer to some run-length encoded packed data, yields a stream of values. Uses the times iterator internally to count off the repeated values.
• menu-options – Provides a dynamic list of items to display in a menu. Yields 2 values at a time – the text to display, and the function to execute when the user selects it.
• xmit-iter – Writes text to the screen with a small delay between each character, to simulate a slow serial connection. An extremely simple loop that can be driven by complex generation logic – including streaming RLE-encoded data with embedded colour information.

#forth #code #essays

Because... functions should be re-entrant by default! They should clean up after themselves! Global variables are bad and must be avoided at all costs! Functions should be “pure” and take all of their inputs as parameters, avoiding hidden dependencies!

All of these ideas of what “good code” looks like are wrong in Forth.

It is actually extremely common for Forth words to rely on implicit context, which is globally accessible through other Forth words. This is often how you build DSLs!

Perhaps you are familiar with the JavaScript canvas API. It's based on PostScript, as are most vector drawing APIs, and PostScript, as you may know, is a Forth-like postfix language for printed graphics. The canvas API has a bunch of implicit state. When you draw a rectangle, for example, you pass in just the position and size. If you want to specify properties like the fill colour, stroke colour, stroke width, line cap style, and on and on and on, you call setter methods before calling the draw function. If you want to preserve the previous canvas state and return to it when you're done, you can explicitly push it onto a stack.

This is one secret sauce to writing small Forth words – you build little vocabularies that all work with some kernel of shared state.

Let's implement Bresenham's line algorithm

I had the idea to implement an algorithm where juggling all of the state on the stack would be a nightmare, to show an example of what this looks like in practice. I've always found Bresenham's line-drawing algorithm kind of awkward – most implementations in C switch between several nearly-identical code blocks depending on how steep the line is. But the core idea is actually very simple, and the awkward near-duplication of the standard C implementation does not have to be reproduced in Forth.

First we will define a simple textual canvas vocabulary:

80 CONSTANT SCREEN-W 
24 CONSTANT SCREEN-H
CREATE SCREEN SCREEN-W SCREEN-H * ALLOT
CREATE SCREEN-BRUSH KEY + C,

: SET-BRUSH ( -- ) KEY SCREEN-BRUSH C! ;
: FILL-SCREEN ( -- ) SCREEN-W SCREEN-H * SCREEN + SCREEN DO I SCREEN-BRUSH C@ SWAP C! LOOP ;
: SCREEN-XY ( x y -- ptr ) SCREEN-W * + SCREEN + ;
: PLOT-XY ( x y -- ) SCREEN-XY SCREEN-BRUSH C@ SWAP C! ;
: PRINT-ROW ( y -- ) 0 SWAP SCREEN-XY SCREEN-W TYPE ;
: PRINT-SCREEN SCREEN-H 0 DO I PRINT-ROW CR LOOP ;

This is ANS Forth – my personal Forths have all been lowercase, I don't usually like all the shouting.

This creates a buffer called SCREEN that is 80 columns wide by 24 rows tall. It also defines the concept of a brush, which is just an ASCII character that is put into this buffer by PLOT-XY. Our line-drawing routine will use PLOT-XY to put “pixels” on the “screen” without caring about what they look like. Kind of a canvassy idea.

Now let's clear the screen:

SET-BRUSH +
FILL-SCREEN 
SET-BRUSH $

I use the + character for “off” and the $ character for “on” because they were about the same width in the variable-width font that my browser picked when plugging this code into jsForth. The trick where SET-BRUSH reads the next character in the code directly is cute but brittle; it only works interactively and will break weirdly in a : definition. WAForth can't handle it at all, it pops up a dialog box asking for you to type a character. Feel free to use 43 SCREEN-BRUSH C! to draw with + and 36 SCREEN-BRUSH C! to draw with $ if you want to follow along in WAForth. Define little helper words for them even, like BRUSH-+ and BRUSH-$. It's not a big problem, don't overthink it, but do make yourself comfortable.

An aside: How to draw a line

So let's talk for a minute about how Bresenham's line-drawing algorithm works. The Wikipedia article has a bunch of math and symbols but at its core it's really very simple. Start with a specific kind of line, that slopes upwards and to the right, but not steeper than 45 degrees.

1. Start at the bottom-left side of the line. Draw that pixel.
2. Move your X coordinate one to the right. Now you need to decide if the Y coordinate needs to move up one or stay where it is.
3. To do that, you keep track of a subpixel fraction; ie. you start in the middle of a pixel (0.5), and increment it by the amount that the line has risen over the last pixel: (y2-y1)/(x2-x1) or dy/dx.
4. If the fraction is >1, move Y up one pixel and subtract 1 from the fraction; the fraction value is now somewhere within the bottom half of the next highest pixel.
5. Now draw the next pixel and go back to step 2 until you end up at the top-right end of the line.

This is very simple! We then layer on just a few simple tricks:

• Instead of always moving along the X axis, for lines that are taller than they are long, we need to move along the Y axis. To do this we simply always move in the direction of the longer side, and run the decision logic along the shorter axis. This way the slope is never steeper than 45 degrees.
• If, for example, the line slopes down instead of up, when we decide whether to move along the Y axis, we need to move down one pixel instead of up. We can handle this by simply incrementing instead of decrementing along the appropriate axis.
• In the olden days, floating point numbers were very slow and integers were fast. Since the “error” value (really a fractional pixel location, but everyone calls it “error”) always has the same denominator, and we don't do anything more complicated than adding more fractions with the same denominator to it, we can just keep the denominator implicit and store the numerator in an integer. We choose 2 * dx (when x is the long axis) as the denominator so that we can easily start exactly on a half pixel (ie. our starting value is dx/2dx, and we increment by 2 * dy every step). It doesn't actually make a huge amount of difference what you use for a starting value though, as long as it's smaller than your implicit denominator then you'll end up with a line that starts and ends where you expect.

That's it! That's the whole thing.

Now back to writing Forth

So, first off, let's define the state that we'll need. Starting and ending X and Y coordinates, the current X and Y coordinates, and the fractional “error” value. Definitely need to remember all that.

VARIABLE LINE-X1 VARIABLE LINE-Y1 
VARIABLE LINE-X2 VARIABLE LINE-Y2
VARIABLE LINE-X  VARIABLE LINE-Y  VARIABLE LINE-ERR

Now we can start defining helper words. Let's write a couple of words to figure out the length of the line along each axis:

: LINE-DX ( -- dx ) LINE-X2 @ LINE-X1 @ - ;
: LINE-DY ( -- dy ) LINE-Y2 @ LINE-Y1 @ - ;

No sweat; just take x2 - x1 or y2 - y1. How about some words to decide which axis is longer, and what direction each axis is moving in?

: X-LONGER? ( -- f ) LINE-DX ABS LINE-DY ABS > ;
: LINE-LEFT? ( -- f ) LINE-DX 0 < ;
: LINE-UP? ( -- f ) LINE-DY 0 < ;

Even if you're not well-practiced reading postfix, I hope it's pretty clear what these are doing.

Now let's define some words for incrementing or decrementing, depending on which direction the line is going:

: LINE-XINC ( x -- x ) LINE-LEFT? IF 1- ELSE 1+ THEN ;
: LINE-YINC ( y -- y ) LINE-UP? IF 1- ELSE 1+ THEN ;
: LINE-INC ( x|y x? -- x|y ) IF LINE-XINC ELSE LINE-YINC THEN ;

LINE-INC is our first and only word to take two values on the stack – the top is a boolean that determines if we're talking about the X or Y axis. We will soon use it in conjunction with X-LONGER? to abstract away incrementing the “long” vs. “short” axis.

: LINE-LONG ( -- p ) X-LONGER? IF LINE-X ELSE LINE-Y THEN ;
: LINE-SHORT ( -- p ) X-LONGER? 0= IF LINE-X ELSE LINE-Y THEN ;
: LINE-LONG-INC! ( -- ) LINE-LONG @ X-LONGER? LINE-INC LINE-LONG ! ;
: LINE-SHORT-INC! ( -- ) LINE-SHORT @ X-LONGER? 0= LINE-INC LINE-SHORT ! ;

LINE-LONG-INC! is a little tricky, so let's walk through it:

• LINE-LONG returns a pointer to either the LINE-X or LINE-Y variable.
• @ fetches the current coordinate along the long axis.
• X-LONGER? pushes “true” onto the stack if X is the long axis (and thus the X coordinate is what's on the stack)
• LINE-INC calls LINE-XINC if X is long, or LINE-YINC if Y is long. This increments or decrements the value, depending on the direction of the line. The new coordinate is the one value left on the stack.
• LINE-LONG ! fetches the appropriate pointer again and stores the new value.

LINE-SHORT-INC! is basically the same, except with an 0= in there as a “logical not” for X-LONGER?. (It didn't quite seem worthwhile to define Y-LONGER? on its own.)

Now let's define some useful words for the error / fractional pixel calculation:

: LINE-LONG-LEN ( -- l ) X-LONGER? IF LINE-DX ELSE LINE-DY THEN ABS ;
: LINE-SHORT-LEN ( -- l ) X-LONGER? IF LINE-DY ELSE LINE-DX THEN ABS ;
: LINE-LONG-ERR ( -- err ) LINE-LONG-LEN 2 * ;
: LINE-SHORT-ERR ( -- err ) LINE-SHORT-LEN 2 * ;
: LINE-INIT-ERR! ( -- ) LINE-LONG-LEN LINE-ERR ! ;
: LINE-ERR-ACC ( -- err ) LINE-ERR @ LINE-SHORT-ERR + ;

LINE-INIT-ERR! defines the initial error value as half a pixel (with LINE-LONG-ERR being the implicit denominator). LINE-ERR-ACC fetches the current error and adds the appropriate fraction along the short axis, leaving the new value on the stack.

: LINE-ERR-INC! ( err -- err ) DUP LINE-LONG-ERR >= IF LINE-LONG-ERR - LINE-SHORT-INC! THEN ;
: LINE-ERR-ACC! ( -- ) LINE-ERR-ACC LINE-ERR-INC! LINE-ERR ! ;
: LINE-STEP ( -- ) LINE-LONG-INC! LINE-ERR-ACC! ;

LINE-ERR-INC! takes the incremented error value, determines if we've overflown the fraction into the next pixel, and if so, decrements the error value and increments the coordinate along the short axis. The updated error value is left on the stack. This is the only place in the algorithm where I chose to use a stack-manipulation word. I could have gotten by without it by just calling LINE-ERR-ACC a couple of times, but it would have made the definition longer and arguably harder to follow.

LINE-ERR-ACC! handles accumulating the error, incrementing the short axis if necessary, and storing the new error. Finally, LINE-STEP puts all the core logic together – increment along the long axis, then decide whether we need to increment along the short axis.

All that's left is to run it in a loop:

: PLOT-LINE-STEP ( -- ) LINE-X @ LINE-Y @ PLOT-XY ;
: DO-LINE ( -- ) LINE-INIT-ERR! LINE-LONG-LEN 0 DO PLOT-LINE-STEP LINE-STEP LOOP PLOT-LINE-STEP ;

: LINE ( x1 y1 x2 y2 -- ) 
  LINE-Y2 ! LINE-X2 ! DUP LINE-Y ! LINE-Y1 ! DUP LINE-X ! LINE-X1 ! DO-LINE ;

The final definition of LINE takes four values on the stack and immediately puts them into variables that are used by all the other words.

IMO, this is what Forth enthusiasts mean when they say things like “write lots of small definitions”, or “the stack shouldn't need to be very deep”, or “you don't need local variables”. There are 24 one line function definitions up there. No individual definition is particularly complicated or hard to read. We do virtually no stack manipulation.

Let's see it in action!

0 0 0 15 LINE
0 0 15 15 LINE
30 15 0 0 LINE
60 15 0 0 LINE
79 7 0 0 LINE
79 7 60 15 LINE
0 15 60 15 LINE

PRINT-SCREEN

$$$$$$++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
$$$$$$$$$$$$$$$$$+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
$+$+$$+$$$$++++++$$$$$$$$$$$$+++++++++++++++++++++++++++++++++++++++++++++++++++
$++$++$$+++$$$$++++++++++++++$$$$$$$$$$$++++++++++++++++++++++++++++++++++++++++
$+++$+++$$+++++$$$$+++++++++++++++++++++$$$$$$$$$$$+++++++++++++++++++++++++++++
$++++$++++$$+++++++$$$$++++++++++++++++++++++++++++$$$$$$$$$$$$+++++++++++++++++
$+++++$+++++$$+++++++++$$$$++++++++++++++++++++++++++++++++++++$$$$$$$$$$$++++++
$++++++$++++++$$+++++++++++$$$$+++++++++++++++++++++++++++++++++++++++++++$$$$$$
$+++++++$+++++++$$+++++++++++++$$$$+++++++++++++++++++++++++++++++++++++++++$$++
$++++++++$++++++++$$+++++++++++++++$$$$+++++++++++++++++++++++++++++++++++$$++++
$+++++++++$+++++++++$$+++++++++++++++++$$$$++++++++++++++++++++++++++++$$$++++++
$++++++++++$++++++++++$$+++++++++++++++++++$$$$++++++++++++++++++++++$$+++++++++
$+++++++++++$+++++++++++$$+++++++++++++++++++++$$$$+++++++++++++++$$$+++++++++++
$++++++++++++$++++++++++++$$+++++++++++++++++++++++$$$$+++++++++$$++++++++++++++
$+++++++++++++$+++++++++++++$$+++++++++++++++++++++++++$$$$+++$$++++++++++++++++
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Lovely!

Now, there is plenty to criticize about this code. It does all kinds of redundant recalculation that in any sane C implementation would have been stashed away into a local, for example. But that's fixable with a little more effort; I might do another blog post where I apply some of Forth's fun metaprogramming tricks to that problem.

#forth #essays #code

I wrote a game on an MS-DOS 286 PC, using only tools I built myself or tools that were available during the era where they were still selling 286 PCs. It's called Neut Tower and you can play it on your MS-DOS PC, in DOSBox, or in your browser. As part of this project, I implemented a Forth system, and built most of my game and its tools using it.

My motivation at the start of the project was this: I was enjoying using my 286. I liked the single-tasking workflow; there were no distractions. I was downloading games and apps and it was fun! So I figured I'd take the next step and write a little game or something.

When I was a teenager, I had a 286, and I tried to learn low-level programming on it because my options were “low-level programming” and “BASIC”, and I had hit my limit with BASIC. Assembly might as well have been Martian to me, but I got a book about C, and I got a book about game programming, and I sort of got some stuff working. But mostly the stuff I tried to do myself from scratch, or port from other sources, didn't work, and I didn't know why. Eventually I also got access to a 486, and then a Pentium, and the internet, and djgpp and Allegro, and suddenly I had an embarrassment of nice graphics and sound libraries and tooling, segment:offset addressing didn't matter, and I never had to worry about trying to understand how Mode X worked ever again.

Twentyish years later, I wanted to learn all the stuff that never quite clicked for me. I wanted to dig into how everything worked, to make sense of the tutorials that once baffled me. I wanted to really understand it all. So I started writing little prototypes, and pretty soon, yeah, I had a cool EGA graphics engine, with two way scrolling of a tilemap and 16x16 sprites drawn on top, running at a decent speed on actual hardware. Everything fell into place one tiny experiment at a time.

With the hardware programming side of things, I learned that my teenage understanding hadn't really been all that far off the mark – my problems weren't so much that I didn't understand the tutorials and resources that were available to me, it was more that I was simply bad at debugging my beginner code, and didn't have the tools or the patience to fix it. With 20 years of professional programming experience under my belt, and a wealth of resources on the internet that explained how things worked in depth, this was no longer an issue.

Then I started to write a game loop in C, and didn't really like it. I knew in the back of my head that, for what I wanted to do, I really wanted some kind of scripting language. And I remembered Forth existed.

In my 20s, obsessed with both the world of programming languages and the world of embedded systems, it was inevitable that I would learn about Forth – it's a particularly uncommon blend of small and powerful, that could run directly on hardware, that people who loved it really loved. I'd tried seriously to learn it but couldn't really wrap my head around it – the weird postfix syntax, the confusing levels of meta. Why could I not use IF statements at the REPL? How was I supposed to remember all these finicky rules? I filed it away as “interesting, but not for me.”

This project was the perfect opportunity to revisit that evaluation. Forth fit the bill exactly – it was a tool that could be built quickly, using minimal resources, and made to do what I wanted, AND I already had a hazy half-remembered foundation from decades ago. I dove headfirst into it.

Relearning Forth was an altogether different experience. It turned out that once I built one myself, I understood it completely. The design of Forth is to write as little code as you possibly can, to make the computer do only as much work as it needs to. When I had to write it all myself, I had to decide – is it worth building this language feature, or can I do without it? Usually I could do without it. Usually there was a tinier way to do it. The code that I had to write wasn't really all that much uglier or worse for it, once I got used to the constraints. And I had proven designs I could pilfer; there are lots of existing open-source Forth implementations to get inspiration from. There are guides for building Forth systems. Doing Forth is not learning an existing language set in stone, it is building a language to solve your problem, and sharing ideas about useful building blocks. Chuck Moore, the inventor of Forth, hated its standardization; thought the goal of portability was absurd, thought everyone should change it as they needed, to fit their problem. He is still trying out new ideas, rebuilding, simplifying, making a system uniquely his own.

So why do I think all this is important enough to write about?

When I was a kid, I had this persistent idea in my head, that computing was a skill I could work at, get better at, and that doing so would allow me to accomplish things that were impossible for me without it. “Once I got good enough”, I could make a computer game, by myself. I could draw the graphics, I could write the code, I could make the music, I could design it all. I could make it and I could put it out into the world and it would be mine, start to finish. Every time I learned something new about computers, got some new piece of software, I gained abilities. I could do things I couldn't do before. My vision of computer literacy is that everyone has this experience, that everyone can learn the skills they want, is provided with the tools they need, to make their imagination real. I have never really let go of this idea.

I'm still trying to find ways to make it true, still trying to explore the different ways that computing can be empowering. Retrocomputing is one avenue for that – people in the past had a lot of good ideas that didn't catch on. And while emulators are wonderful, running them inside a modern computing system makes it harder to experience what using an old computing system really felt like.

When I show people my setup, they are often curious about the qualitative difference between old tools and modern tools; it must be so much harder, right? And... for me, it's really not! I write bugs at about the same rate; I fix them at about the same rate. There are many things I can't do because of resource constraints, but that keeps the scope manageable and makes for an interesting challenge to find cool stuff I can do. The biggest thing I miss is having a second editor that I can use to look at & edit code while my game is running — I have often resorted to taking a photo of some code with my phone so I can read it while I have the game up.

And I gain really valuable things from the constraints. The biggest thing is that there's no alt-tab away from the work – it's so much easier to focus without a web browser instantly at my fingertips. (I'm procrastinating at work writing this right now!) The resource constraints mean I have to focus ruthlessly on solving the problems I have, not the problems I imagine I'll have – there's no perfect, elegant, general solution if I think hard enough, there's only adding things and cleaning up what I've got, one small piece at a time. And I can take workflow seriously as one of those problems! When I'm fed up with the tools that are available for DOS on a 286 (and this happened multiple times!), I make my own that work the way I want, and I'm able to integrate them seamlessly into my engine. I'm able to intentionally craft my environment to be comfortable. I'm no artist, but multiple people have complimented my art – partly, the secret is that 16x16 sprites and tiles can only look so good with a fixed ugly 16-colour palette, so I'm able to focus on broad colour and style choices. But really, if you put me into my ugly, limited pixel editor that's two pages of code but instantly shows me what my sprite looks like in my game, I will mess around until I'm happy. Put me in front of Photoshop with 16 million colours and I will go crazy from decision fatigue; I'll avoid making more art, and I'll get myself stuck.

So for me, the tradeoffs are incredibly worth it. I've spent decades trying to make games as a hobby; I've put out reams of junk – failed prototypes, bad joke games, quick jam games, failed engines, half-finished tools. I've tried every way of making games that I can think of; coding engines from scratch, using Unity, Godot, Love2D, Klik & Play, Game Maker, Twine, Construct, Adventure Game Studio, pygame, Allegro. Some approaches I've had more success with than others, but I've not ever been as happy with anything I've made as I am with Neut Tower. Not as a retrocomputing exercise — as a game.

Neut Tower is done, for now, and I am taking a break from it. (Perhaps someday I will return to it to create the next two episodes.) I'm quickly finding myself using all of these lessons and starting to build some tools for myself in Linux. I don't quite know what they'll turn into yet, but I'm looking forward to finding out, one small piece at a time.

#neuttower #retrocomputing #essays #forth

Forth and Lisp are often spoken of as though they are similar in some deep way. In Lisp circles, you often hear “code is data.” This is generally held to mean “Lisp has macros”, more or less – a Lisp program's source code is a syntax tree made of Lisp lists, that your Lisp program can introspect into and transform into new syntax trees and execute. Your program is literally a data structure.

My Forth code has very few things I would refer to as “data structures”. There is no significant language for defining them – I write one-off words that do pointer arithmetic. I only have a handful, so I haven't felt the need to generalize. It does zero transformation of them – they have been carefully chosen to be directly useful for everything the program needs them for, in-place, as-is.

Instead, the common pattern is that everything is code, which, thanks to Forth's flexible non-syntax, can be made to look a lot like data. Often data is compiled directly into the code that uses it – instead of naming a constant that's passed into a function to do a particular thing, you name a function that takes no arguments that just does the thing. (There are lots of flexible ways to make this sort of thing easy and inexpensive in Forth.) Forth is hyper-imperative to a degree that, as modern programmers, we've largely forgotten is even possible. Even, say, the number 4 is arguably a word executed for its side effects (push the value 4 onto the current stack). Of course, this is how CPUs work, too – you don't have a concept of “4” on its own in assembly, you have the concept of moving “4” into a register, or into memory. The only thing you can tell a CPU is to do things. Forth is the same.

One consequence is that a Forth word that represents a constant is invoked in exactly the same way as a word that makes decisions. What this means is that it is virtually impossible to write yourself into a corner by “hard-coding” something. You can start with the most direct implementation, and expand it into something more flexible as you need to. I often find myself turning a word that was very static into something dynamic, and not having to change any of the code that depends on it. And my Forth has developed lots of facilities for sophisticated decision-making and dispatch. It turns out that most sophisticated decision-making is largely just indirection, and is easy to accomplish even in extremely resource-constrained environments. Many things I used to think of as modern, expensive conveniences – anonymous functions! polymorphism! green threads! – are actually extremely cheap and simple to build, they just... don't exist in C.

In “Programming a Problem-Oriented Language”, Chuck Moore defines “input” as “...information that controls a program.” Forth and Lisp share the idea that, most of the time, it's more powerful and flexible to use the language's parser to read a program's input. Before JSON, there was the s-expression, the universal data structure, and in Lisp, you usually are either using macros to turn that data into code directly, or writing an interpreter for that data. You can often think of a Lisp program as a collection of small, domain-specific virtual machines.

However, Forth doesn't really have a parser; it has a tokenizer, a symbol table, an interpreter, and a virtual machine. Parsing Forth and executing Forth are synonymous; hell, compiling Forth and executing Forth are synonymous. Forth says you don't need a domain-specific virtual machine; you already have a perfectly good machine right here! Why not just solve your problem directly, right now?

You may need sophisticated abstractions to succinctly describe the logic of how your problem is solved, and writing good Forth code is all about investing in those. But Forth makes an argument that most of the data that your program deals with is actually about controlling what your program should do, and making decisions about what your program should do is the job of code.

There are drawbacks to this approach, of course; plenty of things that are inconvenient to express as text, plenty of times I wished I had a “live” data structure I could update on the fly and persist while my program is running, rather than having to exit my program and update my code. But if you can work within the constraints, there is enormous flexibility in it. I'm writing a puzzle game, and while I have a terse vocabulary for defining levels, it's also trivial for me to add little custom setpieces to a given level, to throw in dialogue in response to weird events, to add weird constraints that only apply in that space, because at every step, I have the full power of the language at my disposal. If I'd taken a data-driven approach, I would have needed to plan everything in advance, to design my little problem-oriented VM and and hope I thought of everything I needed. But with a code-first approach, I can be much more exploratory – try to build things, and if they work well, factor them out to be used more generally. Architecture arises naturally from need, as I build.

#forth #essays

• The amount of code required to implement it
• The size of the code that is generated
• The amount of memory used
• The number of features it considers necessary for useful work

It is a language that makes complexity painful, but which reveals that a surprising amount can be accomplished without introducing any. Forth is the opposite of “bloat”. If you've ever been like “Oh my God this Electron-based chat app is taking up 10% of my CPU at idle, what the HELL is it DOING, modern computing has gone MAD”, Forth is there to tell you that computing went mad decades ago, and that programs could be doing SO MUCH MORE with SO MUCH LESS.

WHAT DO YOU MEAN, “FORTH”

There is an expression about Forth: “If you've seen one Forth, you've seen one Forth.” Forth isn't a strictly-defined language, though there is a standardized dialect; it's more a set of ideas that tend to work well together.

In the past month, I wrote a tiny Forth system on a 286 running MS-DOS using Turbo C++ 1.01. It is my first time using Forth in anger, though I read a lot about it 15 years ago. When I refer to my Forth, I am referring to a system literally thrown together in two weeks, written by someone who does not really know Forth that well. It is slow and wildly nonstandard and it doesn't do very much, but I have enjoyed the process of writing it very much. If you are a grizzled old Forth grognard, please let me know if I have misrepresented anything.

WHAT DOES FORTH NOT DO

Here is an incomplete list of things you may take for granted as a programmer that Forth, in its purest form, generally considers unnecessary waste:

• Garbage collection
• Dynamic memory allocation
• Garbage
• Memory safety
• Static types
• Dynamic types
• Objects
• Polymorphic methods
• Closures
• Lexical scoping
• The concept of global variables being in any way “bad”
• Local variables
• The ability to write “IF” statements at the REPL

Most or all of these can be added to the language – the Forth standard, ANS Forth, specifies words for dynamic memory allocation and local variables. There are lots of object systems that people have built on top of Forth. Forth is a flexible medium, if you're willing to put in the work.

But the inventor of Forth, Chuck Moore, literally said, in 1999: “I remain adamant that local variables are not only useless, they are harmful.” In the Forth philosophy, needing to use local variables is a sign that you have not simplified the problem enough; that you should restructure things so that the meaning is clear without them.

WHAT DOES FORTH LOOK LIKE

A core part of Forth is that all functions, or “words” in Forth terminology, operate on “the stack”. Words take arguments from the stack, and return their results on the stack. There are a handful of primitive built-in words that do no useful work besides manipulating the stack.

What this means is that writing an expression tree as Forth code ends up turning into postfix notation. (1 + 2) * (3 - 4) becomes 1 2 + 3 4 - *. Writing a number in Forth means “push that number onto the stack”.

Forth syntax is, with a few exceptions, radically, stupefyingly simple: Everything that's not whitespace is a word. Once the interpreter has found a word, it looks it up in the global dictionary, and if it has an entry, it executes it. If it doesn't have an entry, the interpreter tries to parse it as a number; if that works, it pushes that number on the stack. If it's not a number either, it prints out an error and pushes on.

Oops, I meant to describe the syntax but instead I wrote down the entire interpreter semantics, because it fits in three sentences.

The exception to the “whatever is not whitespace is a word” rule is that the interpreter is not the only piece of Forth code that can consume input. For example, ( is a word that reads input and discards it until it finds a ) character. That's how comments work – the interpreter sees the ( with a space after it, runs the word, and then the next character it looks at is after the comment has ended. You can trivially define ( in one line of Forth.

WHY THE HELL WOULD I USE THAT

There are practical reasons:

• You need something tiny and reasonably powerful, and you don't care about memory safety
• I'm not sure I can think of any others

And there are intangible reasons:

• Implementing a programming language that fits into a few kilobytes of RAM, that you understand every line of, that you can build one piece at a time and extend infinitely, makes you feel like a god-damn all-powerful wizard

Part of the mystique of Forth is that you can get very metacircular with it – control flow words like IF and FOR are implemented in Forth, not part of the compiler/interpreter. So are comments, and string literals. The compiler/interpreter itself is usually, in some way, written in Forth. It turns out that you can discard virtually every creature comfort of modern programming and still end up with a useful language that is extensible in whatever direction you choose to put effort into.

Forth enters that rarefied pantheon of languages where the interpreter is, like, half a page of code, written in itself. In many ways it's kind of like a weird backwards lisp with no parentheses. And it can be made to run on the tiniest hardware!

The mental model for bootstrapping a Forth system goes something like:

• Write primitive words in assembly – this includes the complete Forth “VM”, as distinct from the Forth language interpreter/compiler. The set of built-in words can be very, very small – in the document “eForth Overview” by C. H. Ting, which I have seen recommended as an excellent deep-dive into the details of how to build a Forth environment, Ting states that his system is built with 31 “primitive” words written in assembly.
• Hand-assemble “VM bytecode” for the interpreter/compiler and required dependencies – because of the extreme simplicity of the VM, you can generally program your macro assembler to do this job, and so this can meaningfully resemble the act of simply writing Forth code directly
• Write all new words using the interpreter/compiler you just got running

I say “interpreter/compiler” and not “interpreter and compiler” because they are literally mixed together; there is a global flag that determines whether the interpreter is in “compile mode” or not. It is done this way because it turns out that if you add the ability to mark a word as “always interpret, even in compile mode”, you have added the ability to extend the compiler in arbitrary ways.

WHAT SUCKS ABOUT WRITING FORTH

Any word that takes more than two or three parameters is a nightmare to read or write

Right now in my codebase I have a word that uses two global variables because I cannot deal with juggling all of the values on the stack. This word is absolutely not re-entrant and at some point I'm going to need to rewrite it so that it is, and I am not looking forward to it. If I had local variables, it would be substantially less of a problem. But there's also part of me that thinks there must be some way to rewrite it to be simpler that I haven't figured out yet.

There's another word in my codebase that takes 4 or 5 parameters that I managed to write by breaking it up into, like, 8 smaller words, over the course of writing / rewriting for like an hour or two. I felt pretty proud when I finally got it working, but honestly I think it would have been pretty trivial to write in C with local variables. I miss them.

Shit crashes

Remember the part about no memory safety? Yeah, there's all kinds of ways a wayward Forth system can go wrong. I forgot a DROP once in a frequently-used word and my computer hard-locked when the stack overflowed. (To be fair: my computer was a 286 running MS-DOS, so I was already in a situation where programming it meant rebooting it when I inevitably fucked something up.)

Nonexistent error messages

The only error message my Forth system has is, if it doesn't recognize the word “foo”, it prints “foo?” If, for example, I write an IF statement, but forget to end it with THEN, I don't get a compile error, I get — you guessed it — a runtime hard crash.

WHAT RULES ABOUT WRITING FORTH

It's compact as hell

The majority of words I write are literally one line of code. They do a small job and get out.

It's direct as hell

Building abstractions in Forth is... different than building abstractions in other languages. It's still a really core, important thing, but as building complex / expensive code is so much work, stacking expensive abstractions on top of each other is not really tenable. So you're left with very basic building blocks to do your job as straightforwardly as possible.

You are absolutely empowered to fix any problems with your particular workflow and environment

People turn Forth systems into tiny OSes, complete with text editors, and I absolutely did not understand this impulse until I wrote my own. The Forth interpreter is an interactive commandline, and you can absolutely make it your own. Early on I wrote a decompiler, because it was easy. It's like half a screen of code. There are some cases it falls down on, but I wrote it in like a half hour and it works well enough for what I need.

Everything is tiny and easy to change or extend

Remember when I said I wrote a decompiler because it was easy? Other things I changed in an evening or two:

• Added co-operative multitasking (green threads)
• Custom I/O overrides, so my interactive REPL sessions could be saved to disk
• Rewrote the core interpreter loop in Forth
• Rewrote the VM loop to not use the C stack
• Instrumenting the VM with debug output to catch a crash bug

One of the things on my todo list is a basic interactive step-through debugger, which I suspect I'll be able to get basically up and running within, like, an hour or two? When things stay tiny and simple, you don't worry too much about changing them to make them better, you just do it.

If you have ever wanted an assembly code REPL, this is about as close as you're going to get

Forth is a dynamic language in which the only type is “a 16-bit number” and you can do whatever the fuck you want with that number. This is dangerous as hell, of course, but if you are writing code that has no chance of having to handle arbitrary adversarial input from the internet (like my aforementioned MS-DOS 286), it is surprising how refreshing and fun this is.

THIS SOUNDS INTERESTING, WHAT IS THE BEST WAY TO LEARN MORE

I honestly do not know if there is a better way to understand Forth than just trying to build your own, and referring to other Forth implementations and documents when you get stuck. It's been my experience that they just don't make sense until you're neck deep into it. And it's tiny enough that you feel good about throwing away pieces that aren't working once you understand what does work.

I've found the process of writing my own Forth and working within its constraints to be far more rewarding than any time I have tried working with existing Forths, even if on occasion I have wished for more complex functionality than I'm willing to build on my own.

WHAT HAVE I LEARNED FROM ALL THIS

I'm very interested in alternate visions of what computing can look like, and who it can be for. Forth has some very interesting ideas embedded in it:

• A system does not have to be complex to be flexible, extensible, and customizable
• A single person should be able to understand a computing system in its entirety, so that they can change it to fit their needs

I find myself wondering a lot what a more accessible Forth might look like; are there more flexible, composable, simple abstractions like the Forth “word” out there? Our current GUI paradigms can't be irreducible in complexity; is there a radically simpler alternative that empowers individuals? What else could an individual-scale programming language look like, that is not only designed to enable simplicity, but to outright disallow complexity?

Forth is a radical language because it does not “scale up”; you cannot build a huge system in it that no one person understands and expect it to work. Most systems I have used that don't scale up – Klik & Play, Hypercard, Scratch, that sort of thing – are designed for accessibility. Forth is not; it's designed for leverage. That's an interesting design space I wasn't even really aware of.

The lesson that implementing abstractions as directly as possible enables you to more easily change them is a useful one. And the experience of succeeding in building a programming environment from scratch on an underpowered computer in a couple of weeks is something I will bring with me to other stalled projects – you can sit down for a couple of hours, radically simplify, make progress, and learn.

#forth #retrocomputing #essays