Strong Typing, Unit Testing, and Science

I've doing a technical review of a new book on object-oriented analysis & design that spends several pages discussing strongly-typed vs. freely-typed languages (using Java and Ruby as examples). The author asserts that unit testing does for FTLs what static type-checking does for STLs. I've heard this claim before---in fact, I may even have made it myself once or twice---but the more I think about it, the more problematic it seems.

The argument is that programmers don't actually make type errors very often, so requiring them to specify types all the time slows initial development down. Yes, FTL advocates acknowledge, having explicit types helps with maintenance and extension, but so do unit tests. The latter are more flexible (i.e., you can check a lot more than just variable types in unit tests), and should be written even for strongly-typed code, so why mandate typing?

What's missing from this, though, is any consideration of cost-effectiveness. Which is faster: writing a dozen unit tests, or declaring the parameter and return types of a dozen methods? Which technique catches more errors? And crucially, which catches more errors per minute or hour of programmer time? It's like asking which is more productive: two programmers writing code and tests independently, XP-style pair programming, or having one programmer write code while another writes tests? I think these questions can and should be answered empirically; I also think that the fact so many people feel it's OK to have an opinion one way or the other, without any data to base it on, is one more sign that "computer science" doesn't yet deserve the second part of its name.

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