When Readability Meets Abstraction

Readability

Now, before moving on; the term “readability” is something very subjective and yet we can define some common grounds. So, it’s not that easy to find something that everyone agrees on about readability.

Single-Letter Values and Functions

The first thing I (and maybe many before and after me) discovered was that the rules of naming conventions in an object-oriented language couldn’t be entirely used within a functional environment.

Functional programmers have this habit of giving values and functions very short names. So short that it only consists of a single letter. If we use this habit in an object-oriented language; this is almost always a bad practice (maybe not a for-loop with an aggregated index?).

So, why is this different in a functional environment?

The answer to this can be many things I guess; one of the things that comes to mind is that in a functional environment, you will very often write functions that can be used for any type (generic). Naming such values and functions can be difficult. Should we name it “value”?

In functional languages, the x is most of the time used as this “value”. Strangely, by using x I found the code a lot clearer. So, for values: x, y and z for functions: f, g and h. (Note that these letters are the same as we use in mathematics.)

When we talk about multiple values, we add and trailing ‘s‘; like xs.

Ok, look for example at this following “bind” function for the Either Monad (Rop):

We have written the values explicitly like we would do in an imperative scenario. Now look at the following:

Most of all in the infix operator, the most important part is that we clearly see that the arguments passed in to the “bind” function are flipped. This was something we could quite see immediately in the first example.

After a while, when you see an f somewhere; you automatically understand it’s a function, just like x is some “value”.

Now, I’m not going to state anything; but in my personal opinion, the second example shows more what’s going on with less explicit names. We reach a higher level of readability by abstracting our names, rather strange at first.

Partially Applied Functions

One of the powerful concepts in functional languages that I really miss in object-oriented languages (without off course custom-made functionality like Extension Methods in C#); is the concept of Partial Application. This concept describes the idea that if you send an argument to a function, you get back a function with the remaining arguments. This concept is very strong because now we can decompose for example a three arguments function into three functions with 1, 2 and 3 arguments respectively.

In practice, this concept can really be of help when declaring problems. In my previous post; I solved the Coin Change Kata. In one the properties, I needed to describe the overall core-functionality. In the assertion, I needed to assert on the sum all the coin values:

The “( )” around the operators “+” and “=” makes sure I get a function back with the remaining argument. I could have written the assertion as the following expression:

And I can understand that in the beginning this will maybe be more understandable for you than the previous example. But please note that, with this anonymous function explicitly specified, we have written a “lot” of code just for addition and equality verification.

I personally think that every functional programmer will refactor this to the first example. Not only because it can be written in fewer characters, but it also expresses more what we’re trying to solve. In imperative languages, we typically assign a value to a variable, and that can be used to another variable, … and without you knowing you’ve created a pipeline. I like this concept very much. I don’t have to assign the next result to a value anymore but can just pass it along to the next function.

“For the Change”
“We need to have each value”
“So we can sum all the values”
“And sum it with the remaining value”
“This should be the same as we expected”

Notice that we always use the verb in the front of the sentence. The action we’re trying to express in code now in front of the line by partially applying one of the arguments and not at the end.
Also note that, when we specify the function explicitly, you can’t read the expression in the second example from top to bottom without moving you’re eyes to the right to see the addition or the equality verification; which is actually the most important part of the line.

This is also one of the reasons I like this form of programming.

Yes, I know that it takes some time to get used to this way of writing functions; but I can assure you. Once you have mastered this technique, you would want this in your favorite object-oriented language as well. (That’s one of the reasons I implemented them in the form of Extension Methods).

Infix Operators

One thing that I can’t find a common approach about yet, is the feature of defining your own operators and where to use it. Infix operators can make your code a lot cleaner and more readable; but it can also harm your readability; that’s why it’s probably difficult to define a common approach.

There are already many operators available and by specifying your own operators that looks similar; we can guess what the operator does.

The (|>) pipe operator already exists, and by defining and operators like (||>) or (|>>), we can guess that it has something to do with piping more than one argument, or has something to do with piping and composing.

I didn’t find a global rule to this approach, but I guess it’s something that must be used carefully. If we would define for every function an operator, the code would be less readable.

The (>>=) operator is used for the binding, and so it’s reasonable to define them instead of writing “bind” over-and-over again; because we’re actually more interested in WHAT you’re trying to bind. The same can be said about the (<*>) operator for the Applicative Bind or the (<!>, <$>) operator for the Mapping. When you see the (<|>) you know it has something to do with Conditional Piping since it pipes in two directions (“if then?”). Some operators are well known and so, are probably never questionable to define.

FsCheck defines (.&.) and (.|.) operators to define the AND and OR of Properties. We already know the boolean operators without the dots leading and trailing them, that’s why it’s easier to know what the infix operator does.

The tricky part is when we use too much operators. I would like to use those operators when we’re changing the data flow in such a way that we can reuse it somewhere else. In those cases it’s probably a good approach to define an infix operator.

Conclusion

This small blog post was for me a small reminder of why I write lesser characters and still make more Declarative Code. It was strange at first to think about it. Most of the time in Object-Oriented Languages; when you talk about smaller names, short-handed operators, … you’re quickly end up with an “anti-pattern” or a bad practice while in Functional Programming this is the right way to do it.

Both imperative and functional programmers are right in my opinion. It’s just a way the language allows us to write clear/clean readable code, because that is really what we want to do.