Object Mentor Blog: Functional Refactoring and "You Can't Get There From Here"

Functional Refactoring and "You Can't Get There From Here"

Michael Feathers — Wed, 05 Aug 2009 11:18:00 -0500

I’ve been working in Haskell recently, and I find myself doing much less refactoring. In fact, I rewrite more than I refactor.

I’m not talking about massive refactoring, but rather the sort of micro-refactoring that I do to move from one algorithm to another. If you are working in an imperative language, you can often make micro waypoints – little testable steps along the way as you change your code from one shape to another. You can add a variable, confident that behavior won’t change because you haven’t used it yet, and you can move one statement down below another, changing the order of a calculation if (again) you are confident that the overall computation is order in variant. As I TDD my code, I do those sorts of things. I often refactor by introducing a parallel computation in the same method as the old one, and if the test passes, I knock out the old way of doing things and leave the shiny new one.

In Haskell, however, I don’t do that, and it reduces the amount of time that I spend refactoring. Yes, I rename variables, add parameters, and introduce where-clauses, etc. But, refactoring in Haskell seems different, and I think I know why now. There are two reasons and they sort of intermingle.

Imperative programs are built of little state changing variables, and one of the effects is that you can have lots of little bits changing independently. It’s rather easy to add mutating state variables and have “several calculations in the air” in a method while you are along the way toward reducing it to one. In functional programming, however, you use bigger pieces. Instead of looping, you use map or fold – you end up with terse code which packs a lot of punch.

Here’s a function which determines a position within a document from a column/row coordinate (affectionately named x and y here):

absPosition :: Buffer -> Int
absPosition (Buffer (x, y) contents) = x + lenPreviousLines contents
  where lenPreviousLines = foldr ((+).length) 0 . take y . terminatedLines

The thing to get from this example if you don’t read Haskell is that it is fully compositional. Each of the dots in the definition of lenPreviousLines is a composition operation. We apply the terminatedLines function to a string, and take its output and pass it to the function ‘take y’, then we pass its output to ‘foldr ((+).length) 0’. The net effect (take my word for it) is that we end up with the sum of the lengths of a set of text lines.

That small piece of code performs a rather large chunk of work. It takes a string, splits it into lines, appends a newline to each line, takes y of the lines and then sums the count of their characters. But, to me, that’s not the interesting part. The interesting part is that it is tight. There is no space for a parallel computation, no place where you can perform some computation off to the side and progressively move toward a different algorithm. If you want to change the algorithm you essentially rewrite it – you replace some chunk of that code with another chunk of code.

One of the beautiful things about pure functional programming is that it eliminates side effects. That, by itself, might not impress you, but the thing that it enables is very powerful, when you remove side effects you lose all barriers to composability. It’s easy to make little tinker-toy-like parts which you piece together to do your work, and, in fact, that’s exactly what has happened in Haskell. Most of the time, you can find a little function which will do what you want. You don’t often have to drop down into primitive list operations or recursion. Instead, you have this substrate of little composable bits. We don’t have anything like that in traditional languages. We drop down to loops, assignment and mutable variables all the time.

The end result, I think, is that a lot of refactoring in Haskell is more like rewriting, or (to be precise) it is more like the ‘Substitute Algorithm’ refactoring in Martin Fowler’s Refactoring book. In pure code, there isn’t any extra bandwidth for building up parallel computations. The pieces are bigger, so many refactorings are more like leaps than micro-adjustments toward a goal.

Is this good or bad? I don’t know. I think it is just different. Personally, I’m happy to have higher level pieces, although, I have to admit, I sometimes miss the fluidity of work with more granular primitives. It’s a place you can always drop down to and build back up from. In Haskell, at the micro-level, you have to fix your sights on a new target and rebuild.

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