---
created_at: '2009-08-21T20:06:31.000Z'
title: Scheming is Believing (2005)
url: http://steve.yegge.googlepages.com/scheming-is-believing
author: DTrejo
points: 50
story_text: ''
comment_text: 
num_comments: 20
story_id: 
story_title: 
story_url: 
parent_id: 
created_at_i: 1250885191
_tags:
- story
- author_DTrejo
- story_778339
objectID: '778339'

---
After maybe 13 years of messing around with Lisp, on and off, I'm
finally starting to like it.

Oh, sure, I've been lightly acquainted with Lisp's technical merits (at
least some of them) for maybe a year now. I've been playing around with
various Lisps and Schemes, and reading some books on them. And I've
always done a moderate amount of Emacs-Lisp hacking. But until recently
I never really liked Lisp. Even when I did my little Emacs typing-test
application back in July, I only thought Lisp was so-so.

There were a few things I liked about it, sure. Most languages have a
few areas where they really shine. Well, some do, anyway. But I've
always felt like I was fighting with Lisp and Scheme, and when I really
need to get something done, except in Emacs where you have no choice,
I've always found it easier and more natural to work in Java or Perl or
whatever.

I'm starting to like Lisp, though, and I'm finding I particularly like
Scheme. It's quite different from elisp and Common Lisp. But I still
think of them all as "Lisp", and I think that in spite of all the
squabbling between Lispers and Schemers, they really are still Lisp.

In fact, fighting over them is like arguing the relative merits of, say,
skiing vs. snowboarding. They're both a lot of fun. Skiers and boarders
target each other for jokes, complaints, etc. That's natural, since
they're the only ones on the slopes. They've got an entirely different
set of problems than the kids on the inner tubes down by the parking
lot.

### The Functional Skiing Community

Actually, skiers and boarders aren't entirely alone on the slopes, just
as Lispers and Schemers aren't entirely alone in their problem space.
There's the occasional Haskell-lover on snowblades, or an OCaml person
on telemark skis. Lispers and Schemers consider them part of the family
— it's hard not to when they're there on the same slopes, going off
the same jumps with you, looking weird but competent. But they're a
fairly small minority.

Is it just me, or do those telemark skiers always look like they're
world-class? I'm talking about those [long
skis](http://www.telemarkski.com/) where the heels lift way out of the
bindings, so they have an entirely different style than Alpine/downhill
skiiers. They always seem to be coming down out of the forest above the
runs I'm on. Maybe you have to be world-class if you want to master
something not many others are doing.

They also look pretty lonely. Snowboarders clump together with other
boarders, skiers with skiers, and so on. This is partly just
(sub-)cultural — boarders like the baggy clothes and all that — but also
partly because the natural arcs skiers and boarders make coming down the
mountain are different, so they have an unfortunate tendency to collide
at high speeds. Telemarkers' tracks are different from both. So
telemarkers, at least in the ski resorts I've frequented, seem to be out
on their own most of the time. But they certainly know their stuff.

I remember it took me a few years before I really loved snowboarding. It
didn't happen until I was fairly advanced, and could go down any "sane"
slope (i.e. some double-blacks — no sharp rocks or 20-foot sheer drops
for me, thanks) without fear. I thought I loved boarding early on, but
each year it kept getting better, as I got better.

I never got past intermediate level as a skier. I only did it for 2 or 3
seasons, and always used rental skis, so I wasn't comfortable on
black-diamond slopes. I've been boarding for 12 or 13 seasons now, and
after taking some advanced lessons, my technique got dramatically
better. You never really notice how much energy you're wasting by doing
things inefficiently, at least until someone actually shows you. That's
true of boarding, and programming, and probably just about everything
else as well.

I've sometimes wondered how master-level techniques are discovered for
totally new skill domains. Maybe some people are just naturally good at
it, and a few are articulate enough to show other people what they're
doing. Maybe some people have skills that carry over from other domains,
so initially the best boarders might have been surfers or skiers or
skateboarders. And maybe some people have just figured out that there
are universal concepts like efficiency and economy of motion that apply
to mastering just about anything. Who knows.

Obviously the experts and masters of any skill have a much richer,
deeper appreciation for it than a beginner. I suspect that in general,
that deep appreciation allows them to derive more enjoyment from their
art/sport/craft than people who are less skilled in it. I don't know
that for sure, but it's what all the circumstantial evidence seems to
say. Clearly non-masters can have a lot of fun too. But most things seem
to become more enjoyable as you get better at them, and spend less time
fighting with insufficient knowledge or bad technique. You can focus
that much more on doing cool stuff.

If your art or sport or whatever is demanding enough, so that even the
masters can continue to improve, then it rarely loses its novelty. You
can have fun sliding down a slope on an inner tube, and I suppose some
people can enjoy the experience for their whole lives. But when you
learn how to ski (and it's a lot of painful work\!), new vistas open up
that you probably weren't expecting. To kids on inner tubes, it looks
like skiers are just going up and down crowded slopes, so it's hard to
imagine that it's any more fun than tubing and building snowmen.

Even most skiers and boarders never become skilled enough to experience
the breathtaking beauty and solitude of the back-country. Or the
profound satisfaction of controlling your path through moguls, jumps,
trees, and high-speed chutes. But it just keeps getting more fun, and
it's clear that the boarders better than me are loving it even more than
I am. Struggling takes a lot of the fun out of things.

### Late-Night Scheming

Lisp and Scheme basically snuck up on me. Until very recently, even
though I've been studying and using them both quite a bit, I still
preferred Java and Ruby, and even C++ or Perl, over Lisp for real work.
I just hadn't discovered that back-country wilderness yet. Part of the
key to understanding Lisp is realizing that you won't ever see its
strengths if you just try to write your usual stuff in it. Down on the
beginner slopes, telemark skis and world-class artistry are fairly
useless, because all you can really do is slide along at 10 mph. You
don't need any real sophistication until you try tackling the the
mountaintops.

I stayed up late last night doing programming exercises in Scheme.
That's certainly not what I'd planned on doing. But finally, after
months of reading (books, websites, source code) and experimentation,
something "clicked". All of the sudden I was obsessed with it. It was
almost like I was discovering programming for the first time.

That didn't happen with, say, Ruby. It only took a few days to learn a
substantial amount of Ruby, and I immediately felt happier about solving
the problems I used to solve with Perl. Same with Java: it was just a
better C++, and Perl had been a better awk/sed/sh, etc. I got very
excited about all of them, and I still am, to some extent — you can't
help but love all languages a little, after doing 5 years of nothing but
hardcore assembly-language programming. But learning those languages
didn't feel like rediscovering programming.

I'll confess readily: Lisp me took a long time to learn. I've screwed
around with Lisp for years without liking it much — at least not enough
to want to do any day-to-day programming in it. And even after embarking
on a serious undertaking to become proficient with it, it still took me
more than a year of reading and practicing before I finally started to
really like it. And then it happened more or less all at once. In that
sense, it really was like learning my first language.

One big difference may have been my switching to focus more on Scheme,
recently, but it's hard to say. Maybe it just takes a long time. Or
maybe you don't actually try as hard to learn things until you really
believe, deep down, that it will be valuable. I do distinctly remember
when I decided that I really was going to use Lisp or Scheme for
something major, the books got a lot more interesting. It was a weird,
instant transformation from "academically interesting" to "I want to
learn this stuff right now."

Even after I'd committed to really learning it, Lisp still felt,
compared to languages like Java and Ruby, a bit like trying to go from
tubing to telemarking. It wasn't intuitive, it didn't make me feel
comfortable or happy, and it didn't seem to offer much value over other
languages.

Anyway, once I finally got excited about it, which I'd put right around
"yesterday", I started making my way through the exercises in various
textbooks, even doing those 3-star ones at the chapter ends that nobody
ever does. I also made up my own challenges as I went. I spent an hour
writing three or four versions of quicksort, and I can assure you I've
never before had the urge to implement quicksort for the "fun" of it.

Another exercise from one of the books was to walk a code tree and
compute the lexical-address info for all the identifiers, annotate the
tree with it, and then reconstruct the variable name from its address
later. Um. I typically like to write web sites and games and scripts and
stuff — not pieces of compiler back-ends. But last night I wrote
countless tree-walkers, mini theorem provers, all kinds of things that
I'd heard of but never implemented, except maybe for specific course
projects back in school, after which I promptly and eagerly forgot
everything about them.

Last night, in one night, I did stuff that probably would have taken a
week or two in Java, a language I'm vastly more familiar with. I'll
never know for sure, though, because I'd never want to implement any of
those things in Java. They just wouldn't be fun. I tried doing a few of
them in Ruby, and it wasn't too bad, but it definitely wasn't "fun". The
same algorithm, right after I'd done it in Lisp, felt like work in Ruby.
Evidently the problems that Lisp is immediately suited for, right out of
the box, are problems that are fairly painful in Java or C++, and none
too fun in Perl, Ruby or Python either.

That's one realization, but it's far from the full picture. What's also
become clear is that Lisp is better at adapting to new problem domains
than any other language I've used. And I haven't used other functional
languages like Haskell and OCaml much, but I suspect Lisp beats them in
adaptability as well.

### Evolution is King

Perl began as a scripting language, but it quickly adapted itself (via
libraries and language extensions) to become a good language for Web
programming as well. Perl was really the first flag planted on that new
moon, most likely because of its strong text-processing capabilities and
Unix integration. But Perl tends not to be used as much for the Web
these days; it's nowhere near as popular for building websites as PHP, a
Perl-like language made specifically for the web. They probably wouldn't
have felt the need to create PHP if Perl had been sufficiently
adaptable.

As another example, Perl has never made significant inroads into the
embedded-language space. Perl ought to be an excellent language for
embedding in other applications; i.e. an " app scripting" language,
which is after all very similar to Perl's original purpose. But it turns
out to be a lousy embedded language for lots of reasons, most of them
boiling down to Perl's lack of adaptability, which most people don't
notice because it's got so many shortcuts for Unix scripting and Web
programming. So cleaner languages like Python, Tcl, Lua and even Visual
Basic now have the lion's share of the embedded-language space.

Java has proven itself to be a moderately adaptable language — either
that, or it's just had a lot of people muscling it forward. It began
life intended as a replacement for C++ on embedded devices, detoured as
a rich web-client language, and wound up taking a good deal of the
enterprise-server space (and other domains). And it's well on its way
towards achieving its original goal of being the dominant application
platform for mobile devices. Java must be doing something right.

C is even more adaptable than Java. It's everywhere, and you can do
anything with it, although it really starts to break down at a certain
size system — perhaps a million lines at most. Java scales to much
larger code bases, although it unfortunately eats away much of this
advantage by being inescapably verbose. Like my blog\!

C++ is much less adaptable than C. It's large, nonstandard, ungainly,
and nonportable, and it has horrible linking problems, regrettable
name-mangling, a template system that's too complex for what you can do
with it, and so on, and on. These things all hurt its ability to evolve
towards suitability for new (or specialized) problem domains. C++ was
able to move into the application-programming domain during a temporary
historical anomaly, from the mid-80's to mid-90's, during which software
demands outpaced Moore's Law for a while. The balance is restored, but
C++ is still hanging around like a crusty old aunt, because of all the
legacy app code out there. How C++ made it onto the server-side of the
web, I'll never know. It's hit the Peter Principle for languages big
time: promoted far beyond its capabilities.

### Designing for growth

What makes a language adaptable? Well, languages are how you say things,
so if you need to start expressing new concepts, your language needs to
be able to grow to express them. In particular, you have to be able to
express them cleanly, without having to jump through strange hoops, mix
in a bunch of historical gunk, and write tons of comments that say:
"warning: severe hack ahead". So that rules out Perl and C++.

A language also needs to be well-specified. If nobody's exactly sure how
the language is supposed to work, then it's difficult for people to
build tools for it, develop implementations on new platforms, and build
a community around it. Having a rigorous language spec was a huge part
of Java's success. C++'s spec is very large, but is still filled with
holes. Perl's spec is a printout of Larry's source code, which looks the
same in ascii, ebcdic, and gzipped binary form.

It's easiest to make a solid language specification if the language is
small, orthogonal, and consistent. Again, this rules out both C++ and
Perl. If the language has highly complex syntax and semantics, then
you've got a lot of writing ahead of you, and your spec may still never
be very solid. Java has only moderately complicated syntax and
semantics, and the language specification was created by some of the
world's leading Lisp experts (Gosling, Joy, Steele, and others), so they
were able to do a first-rate job.

In addition to relative simplicity (at least syntactic simplicity) and a
thorough spec, another key element of adaptability is that the language
needs to be extensible. If a particular feature of the language is
getting in your way in some new problem domain, then you need to be able
to change it, or soon you'll be looking around for a new language.

C provides a simple but reasonably effective extension mechanism via its
preprocessor macros. These proved very useful for a wide variety of
problems not addressed by the language, such as feature-conditional
compilation. In the long term, though, it doesn't scale very well, being
neither very expressive nor very well-integrated with the language and
tools.

But at least C has a macro system. Java has absolutely nothing in this
space — admittedly the C preprocessor wasn't something you'd want to
copy, and C++ templates are just about the ugliest thing ever invented
by the hand of man, but that doesn't mean you should leave the problem
entirely unsolved. Now there are all kinds of Java preprocessors, code
generators, huge frameworks like AspectJ, new languages for the JVM and
so on, sprouting up everywhere, all designed to give you the ability to
make Java flex a little.

The lack of a macro system may well be the thing that finally kills
Java, in ten years or however long it's got left. Don't get me wrong: I
think Java's a very strong platform, with lots going for it, and Java
introduced (or at least packaged together) a lot of novel ideas that
people take for granted now. But a language has to bend or break, and
Java's not doing much bending. Very little of the innovation in Java
these days is with the language, and almost none of it has fundamentally
improved its expressive power or its extensibility. Java's turning out
to be the New Pascal.

Python's a very adaptable language, and does well in just about all of
the categories above except for macros. It does offer metaprogramming,
which lets you solve similar classes of problems, albeit not with any
assistance from the compiler. So it's found lots of niches and has a
pretty good user following. Good examples of its adaptability include
Jython (a port of Python to the Java VM) and Stackless Python, which
uses continuation-passing for its control flow. Python's also frequently
used as an embedded scripting language. All in all, it's a pretty darn
good language. Google uses it a lot, or so I've heard.

Unfortunately Python has some flaws that may prove fatal, and which have
undoubtedly kept it from being more widely adopted. One is that the user
community consists mostly of frigid, distrustful, arrogant, unfriendly
jerks. Wasn't it Thomas Hobbes who first observed that communities and
organizations tend to reflect the personalities of their leaders? Python
has other problems, such as the lack of optional static types, although
they're talking a lot about adding that in. But most of Python's
technical problems would be easily surmountable if they weren't such a
bunch of kneebiters.

I could go on comparing other languages, but you get the idea. Times
change, and new problems arise, but languages generally don't evolve
very quickly: they always have backward-compatibility issues, ones that
grow more onerous as time goes by. The only way to keep up is to provide
users with language-extensibility mechanisms.

Of course, defining functions and types is the main way people grow
their languages to fit their problem domains. Those two mechanisms
(functions and an extensible type system) can carry you a very long way.
The Java community has gotten pretty far with Java's simple class
system, mostly through sheer willpower.

But for Java it's beginning to break down. People are using code
generators (EJB, WSDL, IDL, etc.), and they're offloading processing
that should logically have been in Java into XML, e.g. Ant and Jelly, to
cite but two examples. Java has sprouted a powerful 3rd-party
metaprogramming system called AspectJ, and it's on the verge of becoming
accepted by the majority, which means Sun is losing control of the
language. Many other languages are appearing for the JVM, not to mention
templating preprocessors like JSP. Java interfaces and code bases are
becoming so huge that they have turned towards "refactoring tools" as a
way to help them move masses of similar-looking code around.

If Java's so fugging cool, then why does all this stuff exist?

That's not a rhetorical question. I really want to know.

Some people claim that Java is just naturally the best language for
solving large-scale business problems, so Java happens to be tackling
the biggest problems in the world, and it's hitting scaling walls long
before other languages will see them.

That's not what I think. My theory is that Java naturally makes things
large and complicated. So large and complicated, in fact, that it
requires unusually sophisticated automation tools just to keep
normal-sized projects under control.

Take a look at any large Java framework these days (they only come in
one size) and you'll see what see what I mean. JMX is a good random
example, since it just got added to Java 5. It's hundreds of classes,
thousands of interface methods, and several large-ish mini-languages
passed around in String objects. For what, you ask? Well, it provides a
mechanism for you to monitor your app remotely. Er, sort of. It actually
provides a mechanism for you to build remote monitors. I'd have thought
that would be a relatively straightforward problem, and more importantly
one that's already been solved in various ways. But JMX is all-new, and
all-huge, and it's not even generic or reusable, at least according to
its documentation.

Actually, I'll get sidetracked if I spend too long on Java frameworks.
I'll save it for another blog someday, maybe. Besides, I don't want to
come down too hard on Java, because it has a LOT of things going for it
that it does really well. And, ironically, AspectJ may well turn out to
be the thing that keeps Java in the game. I had no idea just how
powerful or mature it was until Gregor came and gave his talk, and even
then his talk didn't do it justice. I just happened to be assigned as
his "buddy" from Dev Services, so I grilled him for half an hour before
the talk, and again for half an hour afterwards, and listened to other
people grilling him as well. I'm convinced now, big time, but even so,
it's going to take a lot of slow, careful experimentation before I feel
really comfortable about its suitability for production work.

And besides, Java's not the only language that has limitations. C++
broke down a loooong time ago. It's just a body shop now. The standard
quantity of measurement for C++ tasks is the "body", and the units
typically range from dozens to hundreds.

### Complexity Boundaries

The reality is that every language has a natural, built-in limit to its
ability to help humans manage complexity before it poops out. Every
language has a natural maximum size for systems that can be written in
that language. Up to that maximum size, things go really well, and you
spend a lot of time focusing on solving the business problem.

As the system grows beyond the language's natural complexity boundary,
people start to spend more and more time wrestling with problems caused
by the language itself. The code base gets huge, and the perpetual bug
count grows linearly (at least) with the size of the code. All kinds of
inertia sets in, as people begin to realize that making certain changes
will require modifying thousands of files, potentially not in an
automated way, because tools can generally help you with syntactic
problems, but not so much with semantic or architectural ones. It starts
to become overwhelming, and eventually progress slows to a trickle.

This has happened to me twice now outside of Amazon. The first time was
at Geoworks. We wrote everything by hand in assembly language: apps,
libraries, drivers, kernel — an entire desktop (and eventually handheld)
operating system and application suite. The system eventually collapsed
under its own weight. Many Geoworks people still don't like to admit it,
but that's what happened. You can laugh it up, saying how foolish we
were to write everything in assembly language for performance reasons.

But you're doing it right now at Amazon. Same justification, same
approach, and already some of the same outcomes. C++ is assembly
language: low-level, non-portable, occupying no useful niche; squeezed
out on the low end by straight C, squeezed on the high end by Java and
even higher-level languages that are now shining as Moore's Law runs
ahead.

I know, I know: you and lots of smart people you know disagree. That's
fine. You're welcome to disagree. I can't blame you: I and everyone else
at Geoworks felt the same way about assembly language. We were doing
great things with it. C was for wimps, and C++ was for Visual Basic
pansies. Performance was King. We all have a blind spot for performance,
you know. All programmers have it. It's in our bones, and we're very
superstitious about it. So I hear you, and I'm not going to try to
change your mind. Everyone has to figure it out for themselves.

I didn't figure it out until it had happened to me again, seven years
later, after building a [very large Java
application](http://www.cabochon.com) mostly by myself. At some
indefinable point, the bulk of my effort had shifted from extending the
application to maintaining it. Never satisfied, I did several months of
deep analysis on the code, and finally concluded that many/most of the
problems were intrinsic to Java, hence unavoidable. I had been immersed
for seven years in blind devotion to Java, seeing as it was actually
kinda nice compared to the old assembly-language gig, and my findings
were surprising and frustrating.

So I spent another year or so of my free time on a massive quest,
searching for a Java replacement. It wasn't as easy as I'd hoped. Lots
of promise, lots of potential, but precious few high-level languages
that actually deliver the vast number of tools and features you need for
building production systens. Given that AOP can help with about half the
problems I was having, Java is still a very solid choice. There's really
only one other contender, one I probably should have been using from the
beginning.

But I won't bore you with the details. The point I was trying to make in
this section is that all languages have a natural system-size limit,
beyond which your innovation starts to slow down dramatically. It
happens regardless of how well you've engineered your system, and
regardless of whether your team is one person or a thousand. Overall
productivity never goes to zero, but that's moot; the point is that you
started out strong and now you're weak.

The natural complexity boundary for any given language is also a
function of your engineering quality, but that can only reduce the upper
bound. The natural limit I'm talking about is the one you hit even if
your system is engineered almost perfectly. Adding engineers can help up
to a point, but eventually communication, code-sharing, and other
people-related issues outweigh the benefits.

You might think your problem domain determines the upper complexity
bound more than the programming language you're using. I don't think so,
though, because eventually all systems grow to the point where they're
huge, sprawling, distributed/networked, multi-functional platforms. Back
in the 70's and 80's, Unix people joked that all applications eventually
grow to the point where they can read mail, and any that don't are
replaced by ones that can. There was some truth to that. Today, systems
grow to the point where they speak Web Services and other protocols, or
they're replaced by ones that can. I don't think your problem domain
matters anywhere near as much as the language, because in some sense
we're all converging towards the same kinds of systems.

What language-level features contribute to a language's scalability?
What makes one language capable of growing large systems, while a
similar system in another language spends all its time languishing in
maintenance-mode?

### Type Systems

If my 18 months of intense study have answered any question at all, it's
what data types are exactly, how they work, and why I'm always
struggling with whether I prefer strong or weak typing.

The design of the static type system is an important determinant of
language scalability. Static type annotations improve system safety (in
the quality sense, if not necessarily in the security sense). They also
help the compiler produce optimized code. They can help improve program
readability if you don't overdo them. And type tags help your editor/IDE
and other tools figure out the structure of your code, since type tags
are essentially metadata.

So languages without at least the option of declaring (or at least
automatically inferring) static types tend to have lower complexity
ceilings, even in the presense of good tools and extensive unit testing.

You might think C++ and Java are strongly typed. You'd be wrong. Ada and
ML are strongly typed. C++ and Java have some static typing, but they
both provide you with lots of ways to bypass the type system. To be
honest, though, I think that's good thing; type-checker algorithms are
often not very smart, and sometimes you need them to get out of your
way. In the end, if your strongly-typed system becomes too much of a
pain, you'll find ways around it — e.g. passing XML parameters as
strings through your IDL interfaces, or whatever.

It might seem odd that type systems yield such great benefits, yet when
you make them too strict, nobody can stand them anymore. The problem is
deeper than you might suspect, particularly if you subscribe to the view
that Object-Oriented Programming is the be-all, end-all of type systems.
Take another look at that JMX interface. It's strongly typed —
superficially, at any rate. But if you dig one or two levels deeper,
you'll see they gave up on the rigorous typing and highly-specialized
32-letter identifier names. At the lowest level, it's all weakly-typed
string parameters and oddly generic-sounding classes like "Query" and
"Role". Almost as if there's a query language frozen in that mass of OOP
interfaces, like Han Solo's face sticking out of the carbonite.

The whole interface is massively overcomplicated, and it seems to
exhibit a sort of struggle between strong and weak static typing, right
there in the same framework. What's going on? Is this really so hard?

The problem is that types really are just a classification scheme to
help us (and our tools) understand our semantic intent. They don't
actually change the semantics; they just describe or explain the
(intended) semantics. You can add type information to anything; in fact
you can tag things until you're blue in the face. You can continue
adding fine-grained distinctions to your code and data almost
indefinitely, specializing on anything you feel like: time of day, what
kind of people will be calling your APIs, anything you want.

The hard part is knowing when to stop. If you're struggling over whether
to call a method getCustomersWithRedHairAndBlueNoses or
getCustomersByHairAndNoseType(HairType.RED, NoseColor.BLUE), then you've
officially entered barkingUpWrongTreeTerritory. Over-zealous typing is a
dead giveaway that someone junior is doing the design. At the other
exteme, not putting in enough static type information is certain to
create problems for you, as you muddle through your nests of untyped
lists and hashes, trying to discern the overall structure.

This is the central problem of Object-Oriented design, and of program
and system design in general.

And if designing your own types is hard, getting a language's type
system right is much harder, because there really is no "right" — it's
different for different people. Some people clean their homes until
every last speck of dust is gone, and some people are a bit sloppier,
but we all manage to get by. It's mostly a matter of personal
preference. This is why advocates of "weak" typing don't see any
advantage to Java's interface declarations and fine-grained primitive
types. They're going to unit-test it all anyway; the type system is just
redundant bureaucracy to them.

Why do you need ints and longs, for instance? A good system should
automatically use the smallest representation it needs, and grow it on
demand, rather than overflowing and introducing horrible bugs, as Java
and C++ both do. Having fine-grained types for numeric precision just
gets people into trouble. In the real world, numbers have distinct,
naturally-occurring types that don't really map to the primitives you
find in popular languages, most of which chose their built-in types
based on machine word-sizes. In nature, we have whole numbers, natural
numbers, integers, rational numbers, real numbers, complex numbers, and
then an infinite chain of matrices of increasing dimensionality. That's
just how it works, and you sort of want your programming language to
work that way too, if you think about it.

### Java's Type System

Many Java advocates are very excited by the notion of
automatically-generated API documentation. Gosh, I guess I am too. But
because JavaDoc does such a great job, and we rely on it so heavily,
many people tend to confuse Java's type system with the doc-generation
system, and they think that you can't have that kind of documentation
without being able to declare Java-style interfaces.

It's simply not true. Java definitely raised the bar on
auto-documentation. But Javadoc's output quality isn't better because of
the interface signatures; the quality is almost entirely due to the
JavaDoc tags, which you fill in by hand. The documentation written by
humans is far more useful than the dubious declaration that a function
takes two ints, or two Strings, or even two Person objects. You still
need to know what it does with them, and whether there are any
constraints on the data that aren't expressed by the type signatures —
e.g. whether can you pass in the full range of 32-bit integers to the
function.

But many Java enthusiasts have latched onto interfaces, and they appear
to think of interfaces as the holy grail of type systems. They know,
deep down, that Java's type system is non-orthogonal, inflexible, and
not very expressive, and they ask questions about how to get around
problems with it on a daily basis. But they're used to assuming it's how
the universe works, so you don't question it, any more than you question
why you have to commute to work when you ought to be able to teleport
there instantly. (The physical universe's constraint system sucks, too.)

It would take a whole book to explain all the problems with Java's type
system, but I'll try to throw out a few examples.

One obvious problem is that Java's type extension mechanism is limited
to defining classes and interfaces. You can't create new primitive
types, and there are severe limitations on what you can do with classes
and interfaces. As a random example, you can't subclass a static method
— a feature that would occasionally be extremely useful, and which is
present in other languages. And a class can't get its own name at
compile-time, e.g. to pass to a static logger. (Jeez.)

One that really irks me: there's no such thing as a "static interface" —
an interface full of static methods that a Class object promises to
implement. So you have to use reflection to look up factory methods,
hardwire class names in your code, and so on. The whole situation is
actually quite awful.

As a result of Java's whimsical limitations, you often find objects or
situations in the real world that are very difficult to express in
Java's type system (or C++'s, for that matter, on which Java's is
modeled). Many Design Patterns are in fact elaborate mechanisms for
working around very serious limitations of the C++ and Java type
systems.

An even more subtle point is that every single element of a programming
language has a type, even though the language doesn't actually recognize
them as distinct entities, let alone typed ones.

Here's an example of what I mean by being able to tag things until
you're blue in the face: Take a for-loop. It's got a type, of course:
for-loop is a type of loop. It can also be viewed as a type of language
construct that introduces a new scope. And it's a type that can fork
program control-flow, and also a type that's introduced by a keyword and
has at least two auxiliary keywords (break and continue).

You could even think of a for-loop as a type that has lots of types, as
opposed to a construct like the break statement, which doesn't exhibit
as much interesting and potentially type-worthy behavior. A type is just
a description of something's properties and/or behavior, so you can
really get carried away with overengineering your type declarations. In
extreme cases, you can wind up with a separate Java interface for nearly
every different method on a class. It's pretty clear why Python and Ruby
are moving towards "duck typing", where you simply ask an object at
runtime whether it responds to a particular message. If the object says
yes, then voila — it's the right type. Case closed.

Ironically, even though every single Java language construct has many
(possible) types, Java itself is oblivious to them. Even Java's runtime
reflection system is only capable of expressing the types provided by
the OO mechanism (plus some stragglers like the primitive types).
Reflection has no visibility inside of methods. If you want to write
Java code that reads or writes Java code, then you have to come up with
your own object model first, and potentially wrestle with complex parser
generators and so on.

Many languages that don't offer you much in the way of static type
annotations (e.g. Ruby, Python, Perl) still have tremendously rich type
systems. They provide you with more flexibility in defining your types,
using far less code, and still providing the same level of safety and
automatic documentation. Declaring a bunch of types doesn't make your
code safe, and not declaring them doesn't make it unsafe. Types are just
helpers, and making the right type choices is a fuzzy art, one that
boils down to taste.

This is one reason OO design (and, by extension, service interface
design) is so difficult, and why interview candidates are often so "bad"
at it. I'll have more to say about types in a future essay, I'm sure.

I went slightly off-course in this section. My goal was to illustrate
that there's life beyond Java, that Perl programmers aren't quite as
disorganized as most Java folks would like to believe, and of course
that a language's type system is one of the most important contributors
to how well the language "scales".

### Language Scalability

I could list other factors that contribute to language scalability: the
complexity of the syntax, for instance, is a real barrier to scaling,
for many reasons. You really don't want a complicated syntax; it'll come
back to bite you. Perl, C++ and Java all have artificially complicated
syntax: too much for too little semantic benefit. Java is the least
bitten of the three, but it still inherits a lot of cruft from C++,
which was designed by a rank amateur. (As was Perl.)

The module system is another big one. Runtime introspection support is
another. In fact, all of the choices made in designing a language,
whether explicit or inadvertent, have some impact on how far the
language will scale before your system becomes too complex for human
beings to keep evolving it.

But all of these contributors pale in comparison to extensibility —
i.e., the extent to which users can customize or change the behavior of
the language itself to suit their needs.

And all languages, bar none, pale in comparison to Lisp when it comes to
extensibility (or adaptability, as I was calling this property earlier).
It doesn't matter how cool or sophisticated or far-reaching you think
your favorite language's extension mechanisms are: compared to Lisp, all
other languages are orders of magnitude less capable of evolution.

### Lisp is DNA

Alan Kay (co-inventor of Smalltalk and OOP) said of Lisp: "it's not a
language, it's a building material." Some authors have called it a
"programmable programming language". Some people say: "it looks like
fingernail clippings in oatmeal." People have in fact said all sorts of
amusing and interesting things about Lisp.

All of the descriptions fall short of the mark, though. And mine very
likely will, too. But I'll try. Or at least I'll try to give you the
barest outline in the next few paragraphs.

Every programming language runs on a machine. That machine is NOT the
hardware, because all languages can be made to run on different machines
— even assembly language, which can be run on emulators. Programming
languages are built atop an abstract machine conceived by the language
designer. This machine that may or may not be very well specified. For
instance, many languages have at least a few constructs whose behavior
relies on the implementation of a system-dependent system call.

All languages have at least part of their underlying machine's
functionality implemented in software. Even C and C++ have software
runtime environments, and of course both languages also rely heavily on
OS services, which are also implemented in software and supported by the
hardware. In fact, all programs run on a tower of machines. Even the
hardware, which you might think of as pretty "low level", is actually
constructed out of smaller machines, all the way down to the level of
quantum mechanics.

OK. Got it. Programs in all languages run on virtual machines.

Languages also provide some amount of syntax: a set of input symbols you
can use for constructing your program, a set of mostly-formal rules
governing how you may arrange those symbols, and a set of
mostly-informal descriptions of how your symbol arrangements will be
interpreted.

Most languages limit you to the symbols in the ASCII character set, for
historical reasons, and they're gradually migrating toward Unicode. But
a symbol could be anything at all, as long as it can be distinguished
from all other symbols used by the language. It's just a unique string
of bits, usually with a predetermined way of displaying and/or entering
it.

The machine interprets your program's symbols according to the language
rules. Hence, all machines are interpreters. Some of the interpreting
goes on in hardware, and some in software. The hardware/software
boundary is flexible. For instance, CPUs have started offering
floating-point arithmetic in hardware, and video cards now offer polygon
rendering and other algorithms that used to be pure software.

With me so far?

Compilers are just programs that pre-interpret as much of your program
as possible. Technically they're unnecessary; you can interpret any
language directly from the input symbols. Compilers are a performance
optimization. They're quite useful, and we grossly under-utilize them,
but talking about performance would take me a bit too far afield today.
I'll have more to say about performance at some point, I'm sure.

Hardware is also a performance optimization, if you separate the notions
of storage and computation. Ultimately computations can be performed by
people or any other kind of physical process that knows how to interpret
your program. When you hand-simulate your program, you're the machine.

So "interpreters" are a much more fundamental notion than hardware or
compilers. An interpreter is a tower of machines, some software and some
hardware, running at different times, all working together to execute
your program.

And your program is just a bunch of instructions, specified by your
arrangement of the language's symbols according to the rules of the
language. Languages and interpreters go hand in hand.

Some programming languages are designed with the goal of being
interpreted directly by the hardware, with as little intervention from
software as possible. C is such a language. This approach has the
advantage of being pretty fast on current hardware. It has all the
disadvantages attendant to premature optimization, but I can't get
started on performance; I've already deleted about ten paragraphs about
it. I'll leave it for another blog.

Some languages, e.g. C++ and Java, are designed to run on more abstract
machines. C++'s abstract machine is a superset of the C machine, and
includes some OOP abstractions. C++ has very complex syntax, partly due
to inexperienced design, and partly because it made many concessions to
hardware performance over people performance. Java runs on a virtual
machine, but it was designed to map very closely to existing hardware,
so in reality it's not so far removed from the bare metal as people tend
to think.

Perl has its own complex, baroque, ad-hoc machine: the Perl interpreter.
Perl has a very complex syntax, with many shortcuts for common
operations.

When you create classes and functions and libraries, you're not
extending the programming language. You're extending the machine. The
language stays the same. If it was hard to say certain things before,
then adding libraries of classes and functions doesn't really help.

For instance, in Java you must double-escape all the metacharacters in
your regular expressions, not to mention create Pattern and Matcher
objects, all because you can't make any changes to Java's syntax. Unless
you want to use the hundreds of non-standard preprocessors that have
sprouted up precisely for reasons like this one.

Another example: you can't write logging, tracing, or debugging
statements intelligently in Java. For instance, if you want to write
something like this:

``` 
 debug("An error occurred with this object: " + obj);
```

where "debug" is a function that checks whether a debugging flag is set,
and if so, prints the message somewhere.

If you do this, someone will happily point out that in Java, function
arguments are evaluated before calling the function, so even if
debugging is turned off, you're doing a bunch of work with that string
concatenation: creating a StringBuffer object, copying in the string
literal, calling a polymorphic toString() function on obj, creating a
new string to hold the object's description, which possibly involves
more StringBuffers and concatenation, then returning the StringBuffer on
the stack, where its contents are appended to the first StringBuffer,
possibly resulting in a reallocation of the memory to make room, and
then you're passing that argument on the stack to the debug() function,
only to find that debugging is off.

Oops.

And that's the best-case scenario. In the worst case, you could trigger
a thread context switch, or a garbage collection, or an unneeded
operating system page-cache fetch, or any number of other things that
you really don't want happening in production because of that debug
line, at least when debugging is off.

There's no way to fix this. Even a preprocessor couldn't do it for you.
The standard hacky workaround is to write something like this instead:

``` 
 if (DEBUG) debug("An error occurred with this object: " + obj);
```

where "DEBUG" is a constant in your code somewhere. This approach is
fraught with problems. The debug flag may need to be shared across
multiple classes, so you need to either declare it in each class, or
export it from one of them. The name of the flag appears right there,
inlined with your code, and there's no way to avoid typing it in
hundreds of places (unless you use AspectJ). And it's just plain ugly.

My third and final Java example: sometimes you really do need multiple
inheritance. If you make a game, and you have a LightSource interface
and a Weapon interface, and behind each interface is a large
implementation class, then in Java you're screwed if you want to make a
Glowing Sword. You have no recourse but to manually instantiate weapon
and light-source implementation objects, store them in your instance
data, implement both interfaces, manually stub out every single call to
delegate to the appropriate instance, and hope the interface doesn't
change very often. And even then, you haven't fully solved the problem,
because the language inheritance rules may not work properly if someone
subclasses your GlowingSword.

The regexp-escaping problem is a lexical problem: an eval-time or
compile-time macro system won't help you, because the lexical analyzer
has already done its dirty work before the parser ever sees the string.
If you wanted to provide a way around this in Java, without using a
preprocessor (which is a hack), you'd need an API that allows you to
interact with the lexer. That's all. Just an API, and a way to arrange
to invoke it before the rest of your code is lexed.

The debug-flag problem is an evaluation-time problem. You can fix
problems like this either by adding support for lazy evaluation to your
language, or by adding a macro system. They amount to mostly the same
thing, except a macro system lets you add some syntactic sugar as well,
which is sometimes appropriate.

The multiple-inheritance/delegation problem is a problem with the
interpreter semantics not being flexible enough. It manifests later than
eval-time, and it's conceivable that you could fix it without needing to
change the language syntax. For instance, if Java simply had a
methodMissing method in java.lang.Object, one that was called every time
someone tried to invoke a nonexistent method on you, then you could very
easily implement your own delegation strategy. It would be far easier to
code, far more resilient to interface changes, and it would even allow
you to abstract your delegation policy into another class, so you could
share it with other classes.

Because no syntax changes are needed, the third problem illustrates a
class of problems that can be solved using metaprogramming, which lets
you change the built-in behavior of classes, e.g. by adding methods or
properties, overriding built-in methods, and so on.

Three problem classes, three different techniques: Lexer (or "Reader")
macros, evaluator macros, and metaprogramming.

C++ lets you do a little of all three of these things with its Template
system, and with its operator overloading, which is a limited (but often
useful) form of metaprogramming. Not enough with any of them, sadly, and
it's too hard to implement what little flexibility it allows you. But
it's much better than C's preprocessor, and it's a thousand times better
than Java's big fat nothing. It of course would be infinitely better,
being a divide-by-zero error, except that we'll give Java some credit
for at least not copying C++'s broken templates.

Ruby and Python offer fairly flexible metaprogramming models, but no
macros or reader-macros. So they're both susceptible to the first two
kinds of problem I mentioned.

Perl has... I dunno. Something. A whole mess of somethings. I know they
don't have macros, since they were discussing adding them on the Perl
newsgroups a year ago. Perl has some metaprogramming features, but
they're relatively limited in scope. And I don't think it has reader
macros, although it may offer some sort of preprocessor.

I hope I've demonstrated that reader macros, compiler macros and
metaprogramming really can make your code a lot smaller, a lot faster,
and a lot more robust. Like any other language feature, you can abuse
them horribly. Unlike other language features, however, you can use
macros and metaprogramming to fix broken language features, and in fact
make the other features less easily abused.

No language is perfect. The perfect language doesn't exist. A language
perfect for one domain can be awful for another. A language that's
pretty good today can be awful tomorrow. Because languages aren't
perfect, they need to provide mechanisms to let you evolve them to suit
your needs. A language's extensibility is one of the most critical keys
to its long-term survival.

Again, Java programmers wouldn't be using XML-based build systems, weird
HTML/Java templating systems, code generators and all those zillions of
other frameworks and tools out there, if Java had been capable of
adapting to meet the needs of those users.

Why don't most language implementers add macros and metaprogramming?
They know that ultimately their language will face extinction if the
users can't evolve it. So what are they thinking?

Sometimes they say that it's to protect the users, or make the language
friendlier to beginners. That's almost always a baldfaced lie, because
they then proceed to pile on horribly confusing features for "experts
only". In a few rare cases (Python, Basic and Cobol come to mind), they
may actually mean it.

Most of the time, though, it's because they've made it way too hard to
implement. The language designer tries really hard to guess which
features you'd like, and they create a nice big abstract machine, and a
bunch of syntax rules (and parsers for those rules), and semantic rules
for interpreting the syntax. After they've piled all that stuff on,
their interpreter and/or compiler becomes horribly complex, and the
language spec is horribly inconsistent, and they spend all of their time
trying to think of ways to fix their busted language.

I tell you: they'd add extensibility if they could. But extensibility
has to be designed in from the ground up, and it makes your system many
times harder to build. As if designing a language isn't hard enough
already.

### Wasn't this blog supposed to be about Lisp?

Yup. And now I think I'm finally in a position to explain why Lisp is
the king of evolution among programming languages.

In stark contrast with every other language out there, Lisp only has two
syntactic forms, atoms (i.e. symbols, numbers, strings) and the
s-expression (which stands for "symbol expression"), which looks like
this:

    (I am an s-expression.)

They can be nested to arbitrary depth:

    (I am an s-expression.
     (I am a sub-expression.
     (We make a tree, actually.)
     (Pleased to meet you!)))

OK, that's Lisp's syntax. Most versions of Lisp add in a small handful
of shortcuts, as long as they don't change the overall tree-structure of
the code.

And Lisp's runtime machine only needs to support a handful of things:

1.  anonymous functions, also called "lambda" expressions
2.  named variables
3.  nested scopes, one per lambda expression
4.  a single control-flow construct called a "continuation"
5.  some kind of I/O

Lisp runtimes provide far more than this, of course, but what I've
described is the core of Lisp, and it's all you need. In theory, you
don't even need special support for strings or numbers; they can be
represented by chains of (and compositions of) lambda functions. All
operators and control-flow constructs, including conditional logic,
loops, exception handling, multithreading, preemptive multitasking,
object-oriented programming, everything can be implemented using only
the five constructs above, and all using the world's simplest syntax.

Try describing the "core of Perl" in anything under a thousand pages —
and you still won't be successful.

The system above gives you more metaprogramming ability than any other
language, but just in case that's not enough power for you, Lisp has
macros: both reader macros and compiler macros.

With reader macros, there's an API to hook into the reader's token
stream and make any changes you like before handing the result back to
the reader. You can implement preprocessors this way — not just \*do\*
preprocessor stuff, but actually implement arbitrary preprocessors for
other people to use. You can change the language syntax however you
like: [remove all the
parens](http://srfi.schemers.org/srfi-49/srfi-49.html) and use
whitespace for indentation, for instance, if that's what's most
appropriate for your problem domain.

With compiler macros, you can pretty much change anything you like about
the language. This scares a lot of people. They prefer their current,
very real pain to some imagined possibility of a different kind of pain.
Weird, but all too common. Me, I'll take the flexibility of macros, only
hire great people, and make sure we all write good code. Problem solved.

I've learned how to use Lisp and Scheme macros, or at least I'm getting
a good feel for them, and they're a LOT easier (and more powerful) than
C++ templates. Scheme macros use pattern-matching and template
substitution. It's similar to XSLT and isn't much harder to learn than
XSLT. Lisp macros are just pure Lisp, and are very easy to learn,
although it can take a long time to fully appreciate them.

The result: Lisp is pure DNA. You can build anything with it, and you
always have the ability to evolve even large existing systems in new
directions. And that's exactly what you need, because your problem
domain is unique.

### But I don't like all those parens\!

I know. I didn't either. I only started getting used to them maybe a few
months ago, and I only started to prefer Lisp to other languages a few
days ago. Don't blame ya.

But with what you know now, it should be clear that Lisp's syntax is a
technical advantage.

For starters, macros need to parse and generate code, right? That's why
C++ templates are so dang complicated. There are a zillion edge-cases to
worry about, and that's just in the syntax; there are also lots of
ill-specified semantic problems with them. If you have a complex syntax,
then it's hard for you to implement macros, and it's hard for people to
use them. Most languages, in trying to give you lots of syntactic
options, have actually limited you permanently to using only those
options.

And Lisp is tree-structured code (and data). It's just lists of lists of
lists... it's way simpler syntactically than XML, and we all love XML,
right? Well, most people evidently do. Even XML, with its allegedly
"ultra-simple" syntax, is still kinda complicated, and working with SAX
and DOM parsers isn't entirely trivial. But it beats working with
C++/Java/Perl/Python parsers hands-down. Trees are just data structures.
We know how to deal with data structures programmatically. But most
languages need to have their syntax converted tortuously into a tree
structure in order to operate on it programmatically, and by then it's
far less recognizable than the original language.

With half a day of work, you could implement XPath expressions to
operate on your Lisp code, and start building your own refactoring and
analysis tools, rather than waiting around for months, hoping someone
else will build them for your Java IDE. In fact, traversing Lisp code is
simple enough to do almost trivially in any language — but it's far
easier in Lisp. So writing Lisp macros and evolving the language to suit
your needs is so natural that you wind up doing it all the time, almost
from the beginning of a project.

The upshot is that your language gradually winds up being tailored
precisely to the system you're building. That's why Emacs-Lisp looks so
different from Common Lisp. It's not so different, really, and it
supports many features of Common Lisp, even though they differ in a few
core areas (as elisp is older, and RMS doesn't care for CL). But
Emacs-Lisp has tons of specialized language features designed
specifically for editors.

In fact, although I don't have firsthand evidence of this yet, I suspect
that the size of Lisp systems tends to grow logarithmically with the
size of the feature set. Or maybe an nth-root function. But definitely
less than linearly, because unlike in Java, where refactoring tends to
make the code base larger, refactoring Lisp code makes it smaller. Lisp
has far more abstraction power than Java.

I noticed ten years ago that even though Perl seems superficially
concise and expressive, the reality is that adding more features to a
Perl system makes the code base grow (roughly) linearly. Need a feature,
add a function. Need a system, add a module. It never seems to get
easier as your system grows. And Java is even worse; the code grows at a
(slightly) greater-than-linear rate as a function of the feature set,
because unanticipated design changes can't be bridged with programming
or macros, and you wind up having to build the bridges using huge
frameworks of objects and interfaces.

So Lisp may seem like it's no better than Perl or Java for small
programs — possibly worse, depending on the program. But that's missing
the point: Lisp only shines when you use it to build a system that would
have been huge in another language. Every sufficiently large problem
domain (from JMX to ordering coffee at Starbucks) is best expressed
using custom mini-languages, and Lisp lets you build them easily and
naturally.

### OK, fine. But I don't want to implement a whole language.

Just because you can implement specialized language extensions in Lisp
doesn't mean that you need to. Common Lisp and Scheme implementations
have huge libraries of carefully-chosen, powerful features. Many of
these features are unavailable in Java and C++, and some can be
expressed in those languages only indirectly.

Hence, ironically, Java and C++ programmers wind up implementing new
languages, very awkwardly, using "design patterns" and other heavy
frameworks, layering on classes and interfaces in an attempt to build a
machine powerful enough to emulate a subset of Common Lisp.

As a language platform, Common Lisp is on par with C++ or Java. It's the
only language I've found, out of the 20 or 30 that I investigated, that
I'd consider to be "production quality". Even Erlang, which is very
mature, still worries me a bit. And Common Lisp is Lisp, which means it
will gradually change its shape to fit your problem space in the most
natural way.

Common Lisp and many Scheme implementations sport powerful compilers,
state-of-the-art garbage collectors, rich IDEs, documentation
generators, profilers, and all the other stuff you've come to expect of
production-quality languages. They have powerful type systems with the
ability to declare static types as desired, to improve performance or
readability. There are multiple commercial and free/open-source
implementations for both languages. Common Lisp is production-quality
and has been for at least as long as C++; Scheme is less ready for
prime-time, although it's gradually getting there.

If I were using Common Lisp, I'd definitely miss one or two features
from Java, and I'd have to take a few days to implement them.

### After all that, I still don't believe you. You're weird.

I know. Don't sweat it. It's just a
blog.

### I disagree with the previous caller. I want to use Common Lisp at Amazon\!

In a word: No.

Languages need large communities on site to do well. And you shouldn't
underestimate the difficulty of learning Lisp. It generally takes longer
to master than even C++ or Perl. Well, about as long, anyway.

We do have a fair number of experienced Lispers scattered about Amazon —
maybe thirty or so, more if you count Emacs-Lisp hackers. But you'd
really need a bunch of them in your group, not just scattered around, in
order to get the right critical mass on your team.

And even then, it would be a highly questionable decision. People would
be watching you constantly, waiting for you to fail, because most people
don't like Lisp and they don't want it to succeed. I was one of those
people not too long ago. I was looking for the perfect language, and I
never suspected the best candidate would be the one that looks like
oatmeal with fingernail clippings. I know \*exactly\* how Lisp-dislikers
feel, and I don't really blame them.

And when you failed, e.g. your service had some sort of highly public
outage (as ALL services do, but that would be overlooked), Common Lisp
would go on trial, and would be ceremoniously burned at the stake, as a
warning to any other would-be Lispers out there. It has happened at many
other companies (Yahoo, NASA and JPL come to mind, but there are many of
them), and it would happen here. If you somehow managed to get a team of
good Lisp hackers together, and you somehow hid the fact that you're
using it, and you were lucky enough to have C++ neighbors who have all
the outages, then you might get away with it.

But if you didn't get away with it, Lispers would hate you for giving it
a bad (well, worse) name. Languages are religions, political campaigns,
and social communities, all rolled into one. Never underestimate the
ability of one language community to gang up and kill another one. Java,
Perl and C++ only thrived here after well over a hundred people per
language more or less simultaneously just started using them, and screw
you if you think they're not doing their job.

Incidentally, none of our core three languages were allowed at Amazon
for the first few years. The only languages allowed were C and Lisp.
Lisp was mostly used for huge, much-loved customer-service application
called Mailman. Mailman was later hastily rewritten as a somewhat
less-loved customer-service application: one that didn't have quite as
much mail-composition functionality, but at least it was in Java, which
solved the embarrassing problem that nobody in CS Apps at the time knew
much Lisp.

The point is that C++, Perl and Java didn't just show up, they barged
right through the front door: first Perl, then C++, then Java, and it
took a LONG time before Java folks were viewed as first-class citizens.
It's taken them even longer to try to integrate with the existing
systems, e.g. the build systems, which were written mostly to solve
horrible build/link problems with C++ that don't really exist in Java.

You really don't want to go there. One individual recently tried doing a
highly visible internal project in Ruby, and it barfed in a highly
public way on its first day of operation; now the Ruby community is mad
because it makes Ruby look bad, when Ruby had nothing to do with it. It
was a poor decision on the engineer's part. Not because there's anything
wrong with Ruby, but because we don't have enough experience with it at
Amazon to understand its idioms and performance characteristics, and
also because very few people have much experience with it here.

Languages need to "bake" for a few years before they become ready for
prime-time at Amazon. They need to be available for personal scripting
and productivity tools, and eventually people will start dabbling with
getting their feet wet with small systems. Over time, as the systems
prove themselves, larger ones are built, and eventually the painful
transition to "trusted, first-class language" completes, typically about
five years after its first introduction.

Today, there are only three languages that have been well-tested enough
in our environment to be considered stable: C, Java, and Perl. And I
suppose some people use C++, even though "stable" isn't a very good word
for the systems produced with it. For general-purpose programming, and
particularly for services that other teams rely on, those are the only
languages \*I\* would use. If a hundred people stood up and announced
they were going to start using Common Lisp, I'd probably stand up with
them — after asking around to see how well they actually knew it.

But it ain't gonna happen. So don't get too carried away. This is just a
speculative blog. Lisp is a cool language, or at least it appears to
have great potential. It's worth a look, and maybe even a second look.
But don't touch, just look\! That Ruby incident has made all the
language enthusiasts a bit paranoid, and we're going to be a little
extra jumpy for a while.

(Published Feb 07, 2005)

Comments

"Compiler macro" actually means something specific in Common Lisp (see
the second paragraph):

<http://olympus.het.brown.edu/doc/gclinfo-html/gcl_3.html#SEC190>

What you refer to as compiler macros are normally called "macros"
without special qualifications. You can probably safely call them
"interpreter macros".

Didn't we actually compile our early C code with a C++ compiler, to get
better typechecking?

Posted by: Derek U. at February 7, 2005 08:54 PM

Xurf kuzl farq lozy\!

You don't understand? Well, I'm taking advantage of a hypothetical
framework for extending English in fundamental ways. Unbeknownst to you,
"kuzl" is part of a new grammatical construct that makes expressing
recursive ideas much more natural.

I have heard enough smart people describe the profundity of their
experiences with LISP to believe that it's a lot more awesome than I
currently realize. But when the selling point is how radically you can
redefine the language, I feel like they miss the value of language
consistency, which translates into being able to read foreign code and
know what the hell is going on.

In your first Java example, you wrote one line of code, and with that
alone you were able to explain exactly what Java does to evaluate that
line. Any experienced Java programmer in the world would be able to tell
you the same thing, just by looking at that one line.

Now pretend that you're up at 2AM trying to debug some system that you
just inherited, the guy who wrote it is no longer with the company, you
know he's a smart guy but sometimes too clever for his own good. And you
have somehow localized the problem to this line:

(make-it-happen (widget-functor asin) (map make-it-happen data))

I don't know enough crazy things you can do with LISP to come up with a
plausible example, but you get the idea. How much other code will you
have to read to even discover what \*sort\* of thing this does?

I believe there is value in language consistency, namely that it makes
it very transparent what your code is actually doing. Not that you
necessarily understand \*why\* it's doing what it's doing, but you at
least know \*what\* it's doing.

If LISP really gives you the expressive power to implement Perl with
LISP macros, then I hardly see how it could be consistent enough to
allow a large group of people to share/maintain LISP code. Unless you
restrain yourself from making these deep extensions to the language, but
then why waste your time writing clunky things like (setq x 1) when you
could just write x = 1?

Posted by: Josh H. at February 7, 2005 11:56 PM

Hey Steve,

Which Scheme environment have you been using? I've been playing around
with a couple of them. PLTScheme, Scheme48/scsh and SISC appear to be
the more complete ones I've found so far.

Posted by: Daniel C. at February 8, 2005 12:03 AM

Josh: I put a comment here that tried to do some more explaining. Then I
re-read my entry, and I see now that I'd just be repeating myself.

I don't think it's possible to be convinced of the benefits of Lisp by
reading about it, or by tinkering a little with it. You just have to do
a bunch of it. Lots. Tons. Then eventually it clicks. That's why I
called this blog "Scheming is Believing."

So if my explanations weren't compelling, and I seriously doubt they
were, then don't sweat it. It's just a blog.

Posted by: Steve Yegge at February 8, 2005 12:25 AM

Daniel — I've been mostly using Kawa, a Scheme for the JVM that compiles
to bytecodes, although I wouldn't really recommend it. It's not a full
Scheme implementation yet — e.g. continuations are upward-only, and it
has an incomplete set of SRFIs, and lots of bugs in general.

Kawa's got a lot of long-term potential, but it's not useful for
production-quality work in either Java or Scheme.

I looked at the info pages for MIT Scheme recently, and they've
implemented a LOT of features from other languages — e.g. list
comprehensions like Haskell's.

For commercial implementations, Chez Scheme is allegedly the best. Fast,
complete, portable, and actively developed.

All the Schemes implement a different feature set, and the code from one
doesn't always run immediately on another. This is a serious problem
with Scheme in general, and I believe it currently renders Scheme
unsuitable for production work.

But I'm gradually working on figuring out if any of them is promising
enough to try to work with.

Posted by: Steve Yegge at February 8, 2005 01:18 AM

In response to Josh Haberman's comment about considering this line of
code:

(make-it-happen (widget-functor asin) (map make-it-happen data))

What would you do if you were staring at this line of code:

if ( (\*self-\>mark\_funcs\[d\])(self, changed\_field\_number) \!=
SUCCESS) return FAILURE;

{pointer to actual Amazon function containing this code}

...trying to figure out why the tax was computed incorrectly\! My point
is that any language can be obfuscated and it seems to be pretty popular
in both perl and C.

Steve - I completely agree that lisp's macro system sets it apart and
gives the language more power. Also, I like the fact that scheme is so
"light-weight" because it comes with a tiny library.

However, big bulky libraries are also power. It can become difficult to
integrate many different libraries into your application if they have
over-lapping problem domains (with different implementations). So,
Common Lisp is very nice in the fact that many common functions are
already available to you.

Of course small vs big libraries is a problem with any language.

So, when is the Scheme Codigo implementation going to be ready?

Posted by: Brian M. at February 9, 2005 10:33 PM
