What to know before debating type systems (2010)
blog.steveklabnik.com
blog.steveklabnik.com
I've been hearing that performance isn't a problem for the last 20 years, yet it seems like I still spend a lot of time waiting for computers and devices to respond. I've worked in mobile and embedded (arguably not a small segment) for a while, and every major product I've released has had a last minute optimization scramble. The growth of these spaces (and now wearable devices) is only making this worse.
On the other hand, a lot of these systems aren't that old. I don't think Android is a Rube Goldberg pile of legacy. But Google acquired a company to get the V8 JS interpreter team for WebKit/Blink, and the Android team just created ART to replace Dalvik. These are smart people who've done a lot of performance measurement and optimization. If the VM didn't matter, it seems like a lot of money and time spent for nothing, right?
Well considering Rust I'm guessing Mr K might have different views now.
> Recently, it was brought up on Proggit that Chris Smith's "What to Know Before Debating Type Systems" was no longer online. This is a really great article, and in an effort to make sure it survives, I've grabbed the archive.org cache and am 'reprinting' it here. If you're into programming languages, read this and level up!
'It doesn't make sense to do the same kinds of exhaustive unit testing in Haskell as you'd do in Ruby or Smalltalk. It's a waste of time. It's interesting to note that the whole TDD movement comes from people who are working in dynamically typed languages.'
Unit testing in dynamically typed languages serves two purposes: 1) to prove code correctness, and 2) to prove code soundness/completeness, to show that the result of a function is correct for most or all input parameters. In statically typed languages 1) is already taken care of by the type system. If your code compiles then there are no glaring type errors in it and your code is correct. However, you still have #2 to worry about.
I work in Scala a lot where there is a static type system. I still have extensive unit tests, and I can't tell you how many times it's saved me when I've changed code in one area of the codebase, thought it was sound and complete, and then immediately become informed it's caused tests to fail, even though it compiled correctly. For instance I'll change code in a model and think that the controller will still behave the same way - and unit testing demonstrates immediately that it doesn't. This is especially true when I didn't write the controller that depends on the model. Testing also helps you rigorously test corner cases - when does this code throw an exception, when does it return a negative number, etc.? It really helps you get a good sense of when a piece of code is done, and move onto the next code.
Unit testing is indispensible both in static and dynamically typed languages, and I don't think lots of coverage is a waste of time in static languages.
assert(len(f(x)) > 0)
Or a more complicated example that I've run into recently. You have a set of predicates, some of which can be evaluated in the browser, some not - e.g. IsFirefox & EverVisitedUrl(url). You then (server side) evaluate EverVisitedUrl(url), get a partial result IsFirefox & True = IsFirefox, and then push whatever is left to javascript `isBrowserFirefox()`.
In python/ruby/etc, you'd need extensive tests to make sure this translation is properly handled. In Scala, if your function doesn't have type `FreeBool[ArbitraryPredicate] => FreeBool[JavascriptEvaluatablePredicate]`, your code won't compile.
Turns out... we don't really do that so much.
With a suitably enlarged definition of (static) type, a lot of tests become type-assertions.
Eg red black trees have interesting balancing requirements: no t
See eg Red Black Trees are another interesting example. A red black tree is a binary search tree, and all its nodes are coloured either red or black. You can not have two red nodes in a row on any path, but all paths from root to any leave have to have the same number of black nodes.
Testing that these two properties hold after an arbitrary number of inserts sounds like a good candidate for a unit tests, and doesn't sound like a type assertion, does it?
See https://www.reddit.com/r/haskell/comments/ti5il/redblack_tre... for how to encode those properties into the types.
In any case, Haskell has great support for unit tests, too. (Because in general you can't and at any rate don't want to encode everything you care about in the type system.)
Have a look at QuickCheck. There are ports for various other languages, too. QuickCheck is a generalization of the table-driven approach to unit-testing: it's about generating those tables automatically, and automatically simplifying any inputs found that lead to buggy behaviour.
These are things I'd have lots of unit tests for.
Here is another example of using static types to fix a problem I constantly run into in Python (adding vectors from the wrong vector spaces together): https://www.chrisstucchio.com/blog/2014/type_safe_vector_add...
By and large, unit tests exist to quickly find bugs.
Anyway, what methods did you have in mind?
OK, actually a lot!
"It's interesting to note that the whole TDD movement comes from people who are working in dynamically typed languages... I'm not saying that unit testing is a bad idea with static types; only that it's entirely appropriate to scale it back a little.)"
What is the difference between "code correctness" and "to show that the result of a function is correct for all input parameters"? In common parlance these are the same thing.
Also, what does it even mean for a piece of code to be sound or complete? Sound with respect to what? Complete with respect to or relative to what?
I think the words that you want are "correct wrt a specification" instead of sound and "total" instead of complete?
Testing cannot prove correctness, period. The proof is a set of unit tests that cover every single input and also a proof that the set of inputs you tested is the entire domain. Basically no in-the-wild unit testing does even the former.
What you mean to say, I think, is, "testing is indispensable when your specification language isn't sufficient for specifying all correctness properties for your code."
Which is about right, but the way that you worded this post was extraordinarily confusing.
Had to double check the year on this one. Things must certainly have changed... For instance, Java is a staple of most CS curriculum. If not Java then often Python. /Never/ have I heard of Ruby being the primary language of choice by a CS department. (Nothing against Ruby, just an observation.)
On the other hand, what is the most popular language/framework for a beginning programmer to learn today? Ruby/Rails or Node? Whereas Java is the quintessential Corporate language.
I'm obviously making some generalizations here. But things certainly seemed to have changed a lot!
Is this not claiming that static typing (and/or lambda calculus) solves the halting problem?
It's worth noting that this is not an either/or problem. Some modern dependently typed languages take a more nuanced approach: they have a less-powerful core with enforced termination¹ and a way to write potentially non-terminating code that's isolated from everything else by the type system. It's the same approach that Haskell uses successfully for IO—it allows IO, but only in a controlled and explicitly delimited part of the program.
In a very real sense, we can treat potential non-termination as yet another effect and manage it accordingly.
¹ Actually, they're even more nuanced than this: programs either have to provably terminate or be provably "productive", which means they produce some new output from new input in finite time. This allows languages to support beneficial infinite loops like the event loop in an operating system while preventing purely harmful busy loops that never get anywhere.
One can add a fix point to the calculus (such as the titular Y combinator), but that introduces inconsistency to the type system.
Immediately contradicted: A static type system is a mechanism by which a compiler examines source code and assigns labels (called "types") to pieces of the syntax, and then uses them to infer something about the program's behavior.
This is possible to do with a program that is understood as being dynamically typed.
Moreover, whenever a type can be assigned to a piece of syntax, it will agree with the dynamic type.
I.e. not "completely different things".
> This is possible to do with a program that is understood as being dynamically typed.
Well and good, but it usually isn't. So the article's point is valid.
1. This debate is not (or no longer) binary. There is a whole spectrum of static typing richness, from dynamic typing to well beyond Idris. The debate, then, is not whether we should be at any of the extreme, but where along the spectrum (including, maybe, the extremes). The interesting question to pose to proponents of very rich type systems, then, is "should we always use the richest type system possible?", and if not, why not? The whole debate -- which, again, is not binary -- hides in two of the questions the author lists in the end: "How easy can it be made to program in a language... ?" Nobody argues that the richer the type system the more properties can be proven (except for one major caveat I mention in item 3). The debate isn't about what character strings containing programs can be rejected or accepted. Programming language design is 5% theory and 100% psychology. What string the compiler accepts is a question for PL theorists. What language is "better" is a question that is 100% psychological, and has absolutely nothing to do with one theory or another. It's a question PL researchers are simply not qualified to answer (Also, even before psychology, it may well be that moving from one point along the spectrum towards richer typing has a cost -- simple, economic cost in development time or in performance -- that is higher than the benefit of extra correctness. Most programs need to be correct only up to a point. Why should they pay for a type system that will make them more correct than they need to be?)
2. The question, "How close can we bring those test suites to the unattainable ideal of never accepting a broken program?" directed at dynamic typing can also be directed at static typing. True, a statically typed language may reject all programs, but practical ones will accept broken ones as well as reject correct ones, simply because there are properties the type system won't verify.
3. Testing isn't the only way to verify dynamically typed programs -- or any program along the typing-spectrum -- for properties that aren't enforced by its type system. There are quite good formal verification methods that don't rely on types. True, the author uses a confusing, self-referential (undecidable? :)) definition for types: "a type is a label used by a type system to prove some property of the program's behavior" that is hard to argue with ("a type is something the type system uses"), but there are "property annotations" in the form of pre- and post-conditions used by verifiers, that aren't normally regarded as types (they don't form a particularly nice algebra), and may be used at any point along the spectrum to prove properties beyond the reach of the particular type system. The implication that types are the only way to prove correctness is wrong.