Productivity in Type Systems

One of the commonly cited drawbacks of type systems is that they can inhibit productivity. I think this depends on your definition of productivity. I can think of two:

1. To write the smallest amount of code in the shortest amount of time
2. To consistently produce working and bug-free code in such a way that it scales as the codebase and team grow over time.

The presence of a type system could certainly hurt productivity in the first case, because languages with type systems often need to be supported by compilers and build tools. I find this type of productivity to be useful when I’m writing small scripts that are run only a handful of times and/or rarely change.

Type systems are invaluable in the second case because they offer benefits that support those dimensions of scaling:

1. They provide a framework within which you can precisely express your ideas. My favorite example is algebraic data types or enums, which are a fundamental construct in data modeling, but are absent in most mainstream languages.
2. They guarantee the absence of certain errors in a well-typed program, particularly large programs which are rapidly changing.
3. Typing information serves as documentation and as a static approximation for how a program behaves, so it is easier to infer intent from code long after it is written.