In his post “Strong typing vs strong testing” Bruce Eckel described the idea, that statically (or strongly) typed languages don’t give you much, because you should verify your programs with tests anyway, and those tests will check the types as well – no need for the compiler to do that (especially if it makes you less productive with the language).

While this looks like a very good point initially, I have some objections.

First, his terminology is not the popularly agreed one. This stackoverflow answer outlines the difference between statically-typed (types are checked at compile time) vs strongly-typed (no or few implicit type conversions). And to clarify this about the language used in the article – Python – this page tells us Python is dynamically and strongly typed language.

But let’s not nitpick about terminology. I have an objection to the claim that static typing simply gives you some additional tests, that you should write anyway.

In a project written in a dynamic language, can you see the callers of a method? Who calls the speak method in his example? You’ll do a search? Well, what if you have many methods with the same name ( iterator() , calculate() , handle() , execute() )? You would name them differently, maybe? And be sure that you never reuse a method name in the whole project? The ability to quickly navigate through the code of big project is one of the most important ones in terms of productivity. And it’s not that vim with nice plugins doesn’t allow you to navigate through classes and to search for methods – it’s just not possible to make it as precise in a dynamic language, as it can be done in a static one.

Then I want to know what I can call on a given object. To do API “discovery” while I write the code. How often, in a big project, you are absolutely sure which method you want to invoke on an object of a class you see for the first time? Go to that class? Oh, which one is it, since you only know it has the calculate() method (which is called in the current method)? Writing a test that validates whether you can invoke a given method or not is fine, but doesn’t give you the options to discover what are your options at that point – what method would do the job best for you. Here comes autocomplete with inline documentation. It’s not about saving keystrokes, it’s about knowing what is allowed at this point in the code. I guess constantly opening API documentation pages or other class definitions would work, but it’s tedious.

Then comes refactoring. Yes, you knew I’d bring that up. But that’s the single most important feature that the tests we write enable us to use. We have all our tests so that we can guarantee that when we change something, the code will continue to work correctly. And yet, only in a statically typed language it is possible to do full-featured refactoring. Adding arguments to a method, moving a method to another class, even renaming a method without collateral damage. And yes, there are multiple heuristics that can be employed to make refactoring somewhat possible in Ruby or Python (and JetBrains are trying), but by definition it cannot be that good. Does it matter? And even if it doesn’t happen automatically, tests will catch that, right? If you have 100% coverage, they will. But that doesn’t mean it will take less time to do the change. As opposed to a couple of keystrokes for a static language.

And what are those “mythical big projects” where all the features above are game-changers? Well, most projects with a lifespan of more than 6 months, in my experience.

So, no, static typing is not about the type checks. It’s about you being able to comprehend a big, unfamiliar (or forgotten) codebase faster and with higher level of certainty, to make your way through it and to change it safer and faster. Type checking comes as a handy bonus, though. I won’t employ the “statically typed languages have faster runtimes” argument. (and by all this I don’t mean to dismiss dynamically-typed languages, even though I very much prefer static and strong typing)

And then people may say “your fancy tools and IDEs try to compensate for language deficiencies”. Not at all – my fancy tools are build ontop of the language efficiencies. The tools would not exist if the language didn’t make it possible for them to exist. A language that allows powerful tools to be built for it is a powerful one, and that’s the strength of statically-typed languages, in my view.