[jxf]

> This is a clear indication of how TDD will slow you down.

Not shown: the part where the critical production bug you introduced was caught by your test suite, thus saving you countless hours of agony, angry customers, and lost revenue.

[nostrademons]

Also not shown: the part where the feature that was exhaustively tested was removed a couple months after launch because requirements changed or the market shifted.

It works both ways, and probably one of the biggest skills to being an effective developer is understanding whether a piece of code you write is likely to be thrown away shortly or whether it's going to live forever and cause umpteen headaches for the maintainer. (This itself is surprisingly counterintuitive: I have seen high-priority code backed directly by an executive thrown away a week after being written because of shifting perspectives within the organization, and I've also seen a one-character typo in a "throwaway" migration script result in restoring a million+ users from tape backup.)

[conistonwater]

"Not doing TDD" absolutely does not mean "not doing testing". You can definitely still test your software, even if you your development process is not test-driven like that. I can't quite understand why this is an issue.

[masklinn]

But then you find yourself back to mempko's inane issue: you'll have to edit your test files alongside your code files, even if you edit the tests after the code.

[chongli]

Instead of writing tests in a separate file, why not express the same logic in the form of types in the lines directly above the code which implements that logic? This has the added benefit of making your code self-documenting and giving rise to powerful tools such as type-guided implementation inference and search.

[masklinn]

Because you probably don't have a type system which comes anywhere near close to what you need to express (I doubt that's even possible).

By all means do leverage your type system as much as you can, avoid writing tests for what you know your type system handles, and (if your type system is expressive enough) use property-based testing to further leverage your type system into essentially fuzzing your functions.

But you'll still need to write tests.

[vertex-four]

How do you write a type which fully describes, for example, "given a user, some content, and various bits of metadata, this function transforms them into a blog post with all the data in the right places"?

[chongli]

You don't write just one type, you write many. The problem you described is pretty straightforward. There are actually lots of examples of how to do this with existing Haskell libraries. What specifically do you want to know about?

[vertex-four]

OK, let's put it this way. I have an entirely arbitrary calculation, taking input A and outputting B. I want to ensure that this calculation is implemented according to specification.

How on earth do you write a type, or set of types, for that that actually bear some resemblance to the spec and don't simply reflect the details of the implementation?

To simplify it to the point of near-nonsense, how would you write a type which says `append "foo" "bar"` will always result in "foobar", and never "barfoo" or "fboaor"? Or that a theoretical celsiusToFahrenheit always works correctly and implements the correct calculation? If you can't do that, how can you do it for more complex data transforms?

[chongli]

This is where dependent types come in. They allow you to write an implementation of append that is correct by construction. Your algorithm is in essence a formal proof of the proposition that `append foo bar = foobar`.

A simpler example is that of lists and the head operation. In most languages, if you try to take the head of an empty list you get a runtime exception. In a language with dependent types you are able to express the length of the list in its type and thus it becomes a type error (caught at compile time) to take the head of an empty list.

[vertex-four]

> Your algorithm is in essence a formal proof of the proposition that `append foo bar = foobar`.

Isn't that literally just implementing the program, though? The point of tests is that they're simple enough that you can't really fuck up, and they describe the specification, not the implementation.

If you have to write a formal proof, what's making sure the proof is actually proving what you intend? And what's the actual difference between this proof and the implementation?

[DenisM]

What type system do you have in mind? Haskell?

[chongli]

Haskell is a start but I was thinking of a system with dependent types such as Coq, Agda or Idris.