The perils of Lisp in production
symbo1ics.com
symbo1ics.com
Whether enforced compile-time strong type checking is a benefit seems to depend on the programmer. It apparently helps some people, it certainly does not help me.
For what it's worth, I've been building "production" (is "production" something you make money on? I find this word increasingly vague) systems with both Common Lisp and Clojure for quite some time now. I prefer Clojure. But both languages are lisps. My thoughts so far: you can build spaghetti code in any language. You can either use a language that lets you run your spaghetti quickly, or one that whacks you on the head repeatedly thus making your spaghetti stiffer and straighter. But you end up with spaghetti anyway.
I agree that it is difficult to write good lisp code. In my code, I spend a lot of time thinking about contracts and data structures. If I am not careful, I end up with problems later on. But using a language like Java doesn't solve that: you just get the illusion of "better code", because your spaghetti design is now codified into neat factories and patterns.
The advantage of using a language from the lisp family is that reworking your spaghetti into something better is much easier, if only because there is so much less code.
And, due to the lisp's nature, you can have static type checking as a library, eg. there's some work on it for clojure https://github.com/frenchy64/typed-clojure, and AFAIK it's based on work already done by Typed Racked/Scheme.
Also I believe that because clojure is a lisp, has very few special forms, is immutable, has nice ns/var semantics and overall focuses on simplicity - you could build quality code analysis tools with relative ease, something that will do search on code for common error paterns, maybe even do verification outside type system with custom DSL. It's something that I would like to explore in few months after I finish my current project.
Once the team gets big, or the code gets so big you can't hold it all in your head, any machine-enforced QC can have a major impact.
(I'm working on a very large Haskell code base now -- the parts that tend to cause trouble are the dynamically typed bits -- they can just go wrong in so many unanticipated ways, and the complexity means its almost unavoidable that devs miss things).
I'm increasingly convinced that to wrangle massive code bases, you need both heavy abstraction abilities (higher order functions, DSLs, algebraic data types, polymorphism), and very strong typing, to keep the complexity under control
You also mention things going wrong in unanticipated ways - this may signal that the problematic code where errors bubble up is not problematic at all - it is called by code written by people who don't really understand what the functions do and who probably didn't write adequate tests for that - because the tests should catch the unanticipated parts. The problematic code is the one calling the parts where errors bubble up. The canary is not responsible for the gases in the mine.
While you may be right that, in order to deal with multi-million-line codebases you need static typing, I'd much rather split that codebase into smaller units that could be more easily managed.
Wearing a straitjacket is often a consequence of an underlying condition that can, sometimes, be corrected.
Sometimes software solves problems which provoke incidental complexity because of sheer size and my experience (albeit not above 500k) tells me that indeed, all bits help, also compiler enforced type checks. I would never bet my life on tests. As you write: "because the tests should catch the unanticipated parts", that's the point: tests never catch unanticipated parts by their very nature. Sometimes, by sheer luck, yes.
No, but calling a function with arguments of the wrong type is something tests would catch.
Or the compiler.
#include <stdio.h>
int main(int argc, char *argv[])
{
FILE *fp = fopen("outfile", "w");
fclose(fp);
do_something(fp);
return 0;
}
int do_something(FILE *f)
{
fprintf(f, "This should work if you know what you're doing");
}
struct WithOpenFile {
FILE *fp;
WithOpenFile(const char *fileName) : fp(fopen(fileName, "w")) {}
~WithOpenFile() { fclose(fp); }
};
int do_something(FILE *f)
{
fprintf(f, "This should work if you know what you're doing");
}
int main(int argc, char *argv[])
{
{
WithOpenFile file("outfile");
}
do_something(file.fp);
return 0;
}
(defun do-something (foo)
(1+ foo))
(with-open-file (file "outfile")
(do-something file))ps My hobby vaporware CL project will probably be called mudball, I'm trying to learn how to design systems with hackability and extreme flexibility in mind :)
The article isn't talking about languages like Java; it's talking about languages with good static type systems.
I don't know if it's possible in Clojure without giving up on Java interop entirely, but good static type systems in other languages can make null pointer exceptions impossible, among other things. If you tell me null pointers aren't a problem for you personally, I'll find that difficult to believe.
I still think you don't need a type system to address this. You could even argue that "nullness" is not a type, it's a data value (an out-of-band data value, shall we say). The way I deal with it is tests for corner cases (I always try to have tests that demonstrate what a piece of code does with null parameters), preconditions and assertions.
I agree that good static type systems can be of help, that is what I meant when I wrote that they seem to help some programmers. I don't dispute that. I dispute the other claim that I understood from the article: that languages that enforce a rigid structure are strictly necessary for "production software".
Right. Unless you use features to escape the type system (such as C's casting, Java's reflection, or C#'s dynamic) which every non-trivial program I've ever worked on did.
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I don't get it.
You could only know the types of the input if the compiler was smart enough and define constraints on the types but as far as I know it's not possible in Clojure.
As an experiment last year I started teaching myself machine learning by implementing the common algorithms in Clojure and Scala simultaneously. I expected Clojure to win out and worked a lot harder in the beginning but after a while I was forced to concede that my Scala code was cleaner, faster, and less buggy, partly because I felt comfortable changing things because I knew the compiler would help me.
Static typing in a programming language is a mechanism for making certain types of non-terminating computations impossible to express in that programming language. The understanding "non-terminating" here includes errors as well (the idea of bottom ⊥ that you'll find in some earlier texts on programming languages semantics, such as Allen's Anatomy of Lisp). Non-terminating computations are equivalent to paradoxes in formal logic (see Curry-Howard correspondence), and the first type system was developed to deal with Curry's paradox (http://en.wikipedia.org/wiki/Curry%27s_paradox) in the first programming language (lambda calculus). Some type systems prevent more types of non-terminating computations, others less. But saying that run-time type assertions are equivalent to a typed programming language, or that types are like contracts or other things just leads to confusion.
"By policy, LISP has never really catered to mere mortals. And, of course, mere mortals have never really forgiven LISP for not catering to them."
I say this as someone who's prototyped several things in Scheme before porting this to other languages.
Now, if we were talking about Python and someone said, "the main peril of Python programmers is that they'll get apple juice and crayon all over everything", that would be insulting!