The complexity goes somewhere.
It's either into lots tests, or it's into something like shuttle style with lots of comments, or it's into a huge QA department, or it's into the type system / DB schema. It could even be going into the org structure!
But something, somewhere is handling the complexity and it is doing so as a partial function to the economic importance of the software to the stakeholders of the software.
> tests
pv_controller.go has 1715 lines. To be generous, we might say half of it is comments. pv_controller_test.go has 359. Hopefully this code is exercised elsewhere in integration tests?
> a huge QA department
That's what you're signing up for when you choose a language that expresses cases mainly using if/then/else, and when you don't feel like testing every case.
> into the type system
Sum types aren't complex, although they're not familiar to everyone in the way i/t/e is. Even a result type (a straightforward example of a sum type, available e.g. in Rust) would simplify a lot of the "if err != nil" boilerplate, and greatly de-indent this code. It would probably also make invalid cases unrepresentable in a few parts of this file, eliminating a few more branches. In fact, a sum type typically requires an exhaustive pattern match, making practices such as their rule "every 'if' statement has a matching 'else'" the default.
My point is, complexity (and economic utility) are not conserved as you choose between these "somewhere"s. A few basic type system features can drastically reduce complexity for the QA team or eliminate comments and cases from the space shuttle.
Still - good on them for this degree of discipline & for so many well-written comments, with clear contracts about what is modified or not. ATBGE.
This example - despise the perplexing celebrations - is a product of the limits of Go
All coding style is a product of the limitations of the language (well, except when it is coding style dictated by the limitations of a different language applied in a cargo cult fashion out of it's appropriate context); and celebrating the choice of how to approach this problem given that it was being done in this language isn't the same as celebrating the language choice. Go would be pretty close to my last choice for anything, but that doesn't stop me from recognizing this as a thoughtful way to apply Go to this problem.
The PV subsystem interfaces with external storage systems, so integration/end-to-end tests are much more useful than unit tests (yes, they do exist).
The main problem here with this "solution" is that any monad looks like every other monad. You can easily lose context and have to rely on naming conventions, which is quite terrible. You cannot spot what the code is doing at a glance.
And if you mess up, the type system and compiler will spout some completely unhelpful message because it parses everything the same.
Code that does very different things should look different, not identical. (Unlike what Lisp and FP people think.) Just think on why we do not use textual buttons everywhere in UI. It's a major reason fewer people accept Lisp than could...
Exceptions are an ad-hoc solution to a sixth problem. You still have the other five. (Ok, it's possible to use exceptions to replace null. But that still leaves the other four).
C does not have exceptions, or any solution to error-checking hell at all. C++ is a notoriously non-simple language. Neither is at all convincing as a counterargument.
> Code that does very different things should look different, not identical.
In a language with monads, code that does things that are specific to error-handling still looks very different from code that does things that are specific to async I/O. But code that does a thing that is fundamentally the same (parametric), such as composition, looks the same. This is the very essence of programming (and indeed of mathematics): "2 + 2" does something that is, on the surface, very different from "3 + 5", yet there is an important underlying commonality. Code that sorts a list of integers is doing something that is, on the surface, very different from sorting a list of strings, but there's an important underlying commonality. Monads just take the same thing one level higher.
I think the major point you're missing here is that the whole point of pushing monads as a core abstraction is the way they shift what "different things" means.
Me: "complexity is not conserved as we choose beween implementations"
You: "So basically complexity is conserved"
Maybe we're getting confused by this word "complexity", so let's break it down into two things: complexity of task handled (COTH) and complexity for programmer (CFP). For a given task of a given complexity, COTH is tautologically the same no matter how you choose to implement. The level of CFP, on the other hand, depends on how you decide to handle complexity. Implementing it in assembly language? High CFP. Implementing it with i/t/e, and commenting loudly your intention to handle all cases? Medium CFP. Enforcing these good, exhaustive standards with the type system? Low CFP. Why does CFP differ? Because the tradeoff matters. In particular, my point was that sum types add a tiny bit of complexity to the language, and remove a TON of complexity from the code. It's not a wash, or even a close contest.
(Notice that I don't make any super-radical suggestions, e.g. that their discipline around mutation/purity should be enforced with types or monads instead of exclamatory comments -- in which case, the CFP added to the language might outweigh the CFP alleviated from the typical file. But my point holds: CFP is not conserved)
Well, unless your computer can read and parse high order proofs over code. Not even Haskell can do that. (It can barely parse F types much less optimize them.) The closest I have come to that feature is Isabelle's simplify and even that is limited.
GCC and Clang can do basic bounds proofs at best and otherwise are tough buggy heuristic beasts. Just look at the trackers.
GHC has a slightly easier job but it's paid for in programming complexity. There are hoops in type system you have to jump to get performant code... and even then the code generated its at best meh quality. There is always some joker telling that it could be compiled for SIMD or multithreaded but that never materialized in usable form.
Of course they can help. Maybe you meant:
> they can't ensure that they are correct
Making the right component tackle the right amount of the right complexity is just a hard problem, and I think when it looks easy it's only because your options were constrained.
I take this more to mean that the logic you're trying to implement has a fixed, non-zero level of complexity (sometimes called "essential" or "inherent" complexity), which forms the complexity floor of your application. On top of that, your implementation adds additional complexity (sometimes called "accidental" or "incidental" complexity), which is not-zero but not fixed.
So, my reading is that in saying "every application has an inherent amount of complexity that cannot be removed or hidden", the law is referring to the essential complexity. Meaning, the law says "some of the complexity is unavoidable in every application" vs. "the amount of complexity is fixed in every application". I do think the name of the law is a little weird, as it implies the latter meaning.
This isn't a dichotomy. My point is that there are clear examples of situations where you aren't just pushing complexity around, but actually achieving great simplifications.
No it wouldn't. The complexity of a pattern can usually be conserved while reducing its length, but for each pattern there is a limit. This is the entire concept behind the Kolmogorov complexity of a system and any patterns that cannot be reduced any further without removing complexity are at their limit already.
This is also related to the idea that you cannot have a universal compression algorithm.
Unless there is one system to rule them all, configured exactly the way it is needed out the box.
At a point you run the risk of just overloading memory with way to many names and entities by merciless chunking, not to mention create a file or function maze.
Inlining works surprisingly well because you do not have to memorize things and can just read them. Theoretically it is a tooling problem, but nobody wrote a good enough "inline" tool so instead everyone relies on incomplete and buggy textual descriptions.
I think you are more or less spot on. Personally I'll mention explicitly (one could argue that you already say this above) that well designed libraries and languages helps you by containing some of the inherent complexity while avoiding to add incidental complexity.
They solve the complexities the average programmer couldn't control on their own.
Most software other than that written for space shuttles and other seriously critical applications.
A colleague of mine works for a telco, and changes to software that runs on satellites takes months to approve and goes through verification stages that include running on simulators and duplicate hardware that is on the ground.
I kind of see it as the opposite: “space shuttle style” is code that adheres to heavyweight rules that most software development has abandoned in favor of a more improvisational style.
But in either case it illustrates that code style rules are desirable, or not, based on the context; you need to understand what purpose rules serve and what trade-offs they involve to understand which rules to use; there's no one-size-fits-all solution.