The Issue with Static Typing
“Shouldn’t we use Scala?” is a recurring question my peers make me. I think it is fair, since I have advocated in the past that Scala has a lot of strong points compared to Java. Furthermore, this question is usually made in contrast to dynamic languages, usually Ruby or Python.
Statically typed languages have as usual claimed benefits that they are faster than dynamic languages, their types provide documentation of the methods and functions, static analysis tools can be more comprehensive and yield better results, and automated refactoring is a lot easier to accomplish and can also give better results. All of these reflect more the current state of implementation and tooling of such languages than of intrinsic property of the type of the language. Steve Yegge has argued this about the speed property, but one can argue for dynamic language that its tooling could use type information from runtime sources, such as unit-testing, to yield similar results .
But some hidden complexities take place when using static typing, which may overthrow any possible benefits coming from it:
- The biggest one is type coupling. For instance, in dynamic languages, renaming an interface is trivial as most interfaces are not even declared, just documented (such as “this must implement less than”). Structural typing can ease this, so can type classes. However, even languages that support these can have problems with other refactorings, such as adding methods to an interface. Paul Graham comments about this a little (on the essay Hackers and Painters):
Everyone by now presumably knows about the danger of premature optimization. I think we should be just as worried about premature design– deciding too early what a program should do.
The right tools can help us avoid this danger. A good programming language should, like oil paint, make it easy to change your mind. Dynamic typing is a win here because you don’t have to commit to specific data representations up front. But the key to flexibility, I think, is to make the language very abstract.
- Some DSLs can’t be built. A common example is the XML DSL. This is because you can’t have in a pure statically typed language a type that accepts any single method call, returning any single possible return value, given any amount of any arguments of any type. In fact, if you do have this type, you in fact have the dynamic type from C#. Dynamic languages usually support this through a mechanism called method lookup alteration and interception, such as those provided by Smalltalk’s doesNotUnderstand, Ruby’s missing_method and Python’s __gettattr__ method.
- Natural complexity. By this I mean that every statically typed languages is a proper superset of a dynamic language of itself. This is easy to see from the theory behind types, as the untyped lambda calculus is just the typed lambda calculus with one type (the brave ones can find more about this on Physics, Topology, Logic and Computation A Rosetta Stone).
- False sense of safety. The types do not guarantee that the implementations maintain the invariants of a type (such as those described by Baraba Liskov). The common example is a comparator interface in Java. Just because a class implements the interface, it doesn’t mean that the compare method is transitive, as required by the documentation. James Iry recently commented on languages with more complex type systems (he actually said a lot more about type systems in general), that contain theorem provers in their compilers, such Agda and Epigram, which can solve this issue. However such languages have other limitations, such as not being Turing Complete. This essentially means that testing practices are still as needed as for static languages (even if you have theorem provers, you cannot be sure without some form of acceptance tests that the problem you are trying to solve is actually the one the customer had in his mind).
- Type variances. This is actually two problems: if your languages does not support them, you have to fall back to type casting, which actually violates type-saftey and static typing in general. If your language supports it, you have to know one more concept, and when to apply it. It may not be always clear when a type should be co-variant or contravariant. This is further complicated by the fact that types with side effects (such as mutable objects) have special rules about this (further about this can be found under Variance of Mutable Types, from Programming Scala). Also this concept is so common that functions are naturally covariant on the return value and contravariant on the parameters. Scala’s two argument function documentation shows this explicitly.
The last two issues are very diminished for languages without subtyping, but these have deeper problems as, in order to relinquish subtyping, you also have to give up on any possibility of code reuse possibility from ad-hoc polymorphism.
It might seem that some points were left out, but these are usually the problem of a particular language, which are commonly and mistakenly considered to be a problem of static typing in general:
- Lack of metaprogramming support. Of course C++ has templates, which means that most people know that this is false for all statically typed languages. However, a variant of this issue is: type safe safe metaprogramming. This is also not true. Haskell, for instance, has a type-safe macro system. Note that you cannot make type-safe runtime metaprogramming in general. For instance: even though some languages allow you to create interfaces that do not exist on compile time, the only way to invoke methods from these is through non type-safe ways (such as reflection).
- Verbosity. Scala is the canonical counter-example (Scala can be as terse as Clojure in some ways). The more type-inference you have, the less type annotation you have to write. This doesn’t necessarily make reading it easier, but IDEs can help here. On the other hand, it will never be harder to read than dynamic languages.
Going back to the question that originated this discussion: static types can come in handy, and they do have better tools these days. But they do bring complexities way beyond having to type a few extra characters. And these should not be taken lightly when considering to express code in a statically typed language.