Casey makes the point that you don't have to hand-tune assembly code, but instead just write the simpler code. It's easier to write, easier to read, and runs faster too!
If there's something wrong with that advice, I can't imagine what it is...
If there's something wrong with that advice, I can't imagine what it is...
It absolutely is, on toy problems like the one described in the article.
It very frequently is not when embedded in much larger domains as part of large projects maintained over years by teams.
The claim that "Clean Code" scales better or allows for more maintainable software hasn't been proven by anyone, and everyone with enough experience has worked with several counter examples.
The problem of code maintainability is not solved by this coding philosophy.
I'm totally onboard with prioritizing readability over performance for most code, but the style in the book has a lot more tradeoffs than it discloses, and you often don't really appreciate that until you are trying to debug if/how A transitively calls Z in a 10 million line codebase.
It's really hard to have a constructive conversation about this though since it's so subjective, any example is too trivial, and any real system is too large.
If you can't point to an actual example, I don't think you have a solid case.
However, the bigger your task gets the more value there is to polymorphism and in general the smaller the percent of total time goes to the polymorphism overhead.
And note that his attack is only on polymorphism, not the other aspects of clean code. I strongly suspect the compiler optimizes away much of the clean stuff I do but I have never checked. I also find profiling easier on cleaner code, it makes it very obvious where the time sink must be and thus what warrants expending effort to improve. Profiling almost always shows the vast majority of time going into the unavoidable (say, disk reads) and a small number of other routines. Spend your optimization effort on the spots that need it because 99+% of your code doesn't run often enough for it to matter.
One of the nice things about some of the clean code concepts he uses is that (as he shows) you can tactically step back from them in key, performance critical areas and reap these wins.
If you stay too low level you get lots of tangled spaghetti code with major performance problems and no obvious way forward besides "make it better."
Using procedures/functions is not exactly "low level". Using switch is not low level. Lookup tables are something you have to do in high level code all the time.
Sure he could have used much better variable naming (CTable?) and probably documentation, but code-wise there's nothing that screams low level there.
I would consider most of his replacements lower level than typical the clean code practices he critiques (especially the ones like iterators that he mentions but avoids in order to steel man the clean code side a little bit), not the lowest level possible. They take into account how the machine actually works and avoid additional indirection which is why they perform better.
Take Listing 27, getAreaUnion for example:
f32 const CTable[Shape_Count] = {1.0f, 1.0f, 0.5f, Pi32};
f32 GetAreaUnion(shape_union Shape)
{
f32 Result = CTable[Shape.Type]*Shape.Width*Shape.Height;
return Result;
}
{-# LANGUAGE OverloadedRecordDot #-}
data Shape
= Square { width :: Float, height :: Float }
| Rectangle { width :: Float, height :: Float }
| Triangle { width :: Float, height :: Float }
| Circle { width :: Float, height :: Float }
cTable :: Shape -> Float
cTable shape = case shape of -- The "lookup table" or "array"
Square {} -> 1
Rectangle {} -> 1
Triangle {} -> 0.5
Circle {} -> pi
getAreaUnion :: Shape -> Float
getAreaUnion shape = cTable(shape) * shape.width * shape.height
The stuff proposed in the post is not rocket science, it is a very straightforward implementation of tagged unions. Instead of fetching a vtable and jumping to a value there, he proposes to branch on the tag. This is essentially dynamic dispatch on a known set of types.
Additionally, he shows that this can result in speedups greater than a factor of 1. Any program that wants low latency or high throughput can profit from this observation.
This way of programming is by no means the one to rule them all. It has different advantages and drawbacks; none of which have anything to do with the percieved intelligence of the programmer or later consumers, for that matter.
An objective disadvantage of this style is, that the program can't interface with code, that hasn't been written yet, as a caller. Another disadvantage is that the size of the tagged union is defined by its largest "subclass".
In the end, what he has shown is that speed is often a compromise made unnecessarily. This doesn't really have to do with clean code anymore, as I can see how a compiler could implement what he is angry about with virtual functions in every situation where his style is applicable.
Casey has had a similar thing about the windows-terminal and somewhere in his videos a different, yet arguably worse, problem comes to mind: a lot of libraries do not care about performance enough. If you write a program and care, you may run into the problem that the library you use is your bottleneck. If this library is hard to replace (imagine needing a rocket-scientist), then you are done for. In that specific case it was DirectWrite and some other Windows-API that were slow. So if, for one reason or another, the windows team was required to use both, they'd have a hard limit on how fast they could go, just due to that. There is no "being smart" or "requiring a genious" involved in the forced/strongly recommended library here.
It will start getting really annoying when you try to add shape ‘hexagon’ and need to figure out all the places where a shape can potentially be used, just so you can update the switch statements.
The author of the video discovered that C++ compiler is dumb when it comes to optimizing virtual method calls (that instead of bare virtual method calls he had to help the compiler to guess the right conditions where these virtual calls could be replaced with guessed static calls). Essentially, all that his video is saying is: "virtual calls bad if-else good". Which is like what every C++ game-dev thinks after few years on the job. Which is amusing in how short-sighted it is, and sometimes even more amusing to discover the "solutions" created by such C++ game-devs that are aimed at replacing C++ objects, but do it in a way that's even worse than C++ original design (who would've thought that to be possible!?)
Conversely, in a codebase organized by objects it's not clean to add an extra method to the base class and each subclass. You have to write an external function and switch over every known subclass inside it, which is also very ugly and will also break when you add more subclasses.
The two designs are actually the duals of each other. Someone compared it to rows vs columns and it's a great comparison.
In OO, the methods are columns and each new row is a new subclass implementing them.
In FP, the types are the columns and each new row is a function that switches over the possible types.
https://journal.stuffwithstuff.com/2010/10/01/solving-the-ex...
He also discusses it in his book Crafting Interpreters.
If your cases are defined externally, and you need to be forwards compatible, omitting a default is wrong.
The Swift language specifically added `@unknown default` for switching over enums.
But we can just re-up the problem by adding 100 different shapes instead of the one. Now you have switch statements with 104 cases each spread through your codebase.
This is the "expression problem": https://en.m.wikipedia.org/wiki/Expression_problem
ITs still possible to get a bottleneck in assembler.
Whatever language is used, executable code still needs to be profiled using tools as described here.
https://en.wikipedia.org/wiki/Profiling_(computer_programmin...
Casey's definition of simple actually reminds me of the cliché by Rich Hickley. It's simple, but it's not necessarily easy.