When I write Rust code I basically never have to explicitly free anything outside of FFI code dealing with C pointer or the like. The most straightforward way to allocate anything in Rust is to reify a Box which frees its contents when it's dropped. The data is freed when I remove it from containers or when a Box gets dropped. The closest I get to garbage collection is using a reference-counted pointer here and there (and only after careful consideration).
I really don't see what complexity the GC removes in this situation, besides letting you write code without having to care about ownership which, as I stated earlier, I consider to be an antipattern.
>"just do this X and you don't need to use GC" is a reason people use GC languages, because they don't want to think about or write this "X"
A lazy programmer is a good programmer but it's also important to recognize when something can't be pushed under the rug. I don't want to think about or write documentation and unit tests either, yet here we are. If I had to maintain an application and I ask the coder "when exactly are these objects deleted?" and they answer "dunno lol, I let the GC figure it out" I'd be extremely worried.
If you haven't heard of it, you might be interested in the Waterbed Theory of Complexity[1]. The idea behind it is that it's not that you can't push down complexity in an area, but often that complexity just pops up in a different area. For example, you can do away with the vast majority of allocating and freeing memory, but the complexity of doing that pops up again when you start having to tune your GC or use very special patterns to avoid/minimize GC freezes.
That's not to say there's not a benefit to that sometimes. If you can push the complexity away from the majority of use cases to a few special use cases, that might be a net win. It doesn't always feel like that though if you're the person stuck trying to coax that last few percent of performance optimizations out of a runtime that only gives you so many levers and dials to work with.
I think some of the same concerns that make a dynamic/scripting language a poor choice compared toa compiled and static one are the same things that might make a GC language a poor choice compared to a manually memory managed one, and it's just a matter of scale that separates them. Is performance important? A scripting language might be a poor choice. Is performance really important? Then a GC language might be a poor choice. On the other hand, if I'm writing some program to run correctly once or twice ever, and it might actually take more tome to write than it will ever run for (e.g. a script to parse and/or transform data on disk for me to fix a problem), then is anything really gained from manual memory management? Writing that in Perl or Bash is a valid option there, and that's about as far away from memory management as you can get. For portions of my career, I've spent half or more of my time writing programs like that to help with sysadmin tasks.
So that is to say, when we push down a "bump" of complexity in one place, seventeen bumps at least as large can crop up elsewhere. Moreover, that seventeen is just today; we might have paved the way for more such bumps now being necessary going forward as functionality is added, whereas if we kept the original bump, it would stay the same. Water is not a good model for complexity because it is incompressible for all practical purposes; if we push down a liter of water here, the places where it pops up add up to just a liter.
For exmaple, virtual memory is considerably simpler than individual modules of a program implementing a scheme for swapping code and data to disk and back.
I think you've taken the metaphor about a waterbed and design advice a bit too literally. :)
When you push complexity down in one area and it pops up in another, there's no guarantee that it's of the same overall magnitude, as it would be in a real waterbed. Sometimes it's larger, and sometimes it's smaller.
The same idea applies to whether we should all write assembly or use a higher level language to accomplish our computing needs. We push down the complexity of knowing exactly what the processor is doing at any one moment for a easier to manage overall view of what we want to accomplish. Overall, the net effect is a lessening of complexity for most people, but for those that want or need to know exactly what is going on, there more complexity. Still, overall I think the net effect is less complexity for most people, vastly outweighing the time and effort a few put into figuring out why something isn't as expected.
On the other end of the spectrum, using a dynamically typed scripting language might save people a lot of time initially, or when prototyping, or on smaller programs, but as those programs become larger, the lack of constraints (which provide a small but immediate complexity hurdle) can build up and overwhelm a large project that might otherwise had an easier time if some more constraints were required along the way.
No one tool or paradigm is perfect for every task, and we should not expect one to be. We don't usually commute in dump trucks, and we don't usually haul lots of debris in compact cars. I see no reason why it should be any different for programming languages. Sometimes all you need is a 10 line bash script, and given that information, I doubt there's a huge level of complexity that's going to rear its head later because I didn't write it in some lower level language.
If that isn't taken literally, it informs of nothing we don't already suspect. It tells us that for each functional requirement, there is at least one piece of code in the system somewhere. If we remove these lines of code from one place, or places, something has to be added elsewhere (possibly way more lines, or way fewer) so that the requirement remains implemented.
It informs you of nothing you didn't already suspect. I think it's useful to remind people of something that's fairly obvious ans self explanatory if you think about it, but not everyone does, and having an easy and slightly odd metaphor to point to helps the point to get across. The fact that you think it's obvious is actually one of its major benefits. You can immediately start exploring the consequences of it instead of spending time proving it. Honestly, of all the criticisms to level at a metaphor, "too obvious" isn't one I would consider worth bringing up. Obvious metaphors are used to good effect all the time.
Edit to address your prefixed paragraph:
> The waterbed theory in fact explicitly states that the amount of complexity is preserved no matter how it is distributed.
If you read carefully, it says that the minimum level of complexity may not be reduced. Who is to say the minimum level of complexity has already been reached? Or that pushing down a level above the minumum in some area won't cause only the minimum level to rise elsewhere (or vice-versa)?
You're absolutely right, in the GC context you:
(1) Have to manually reference count / manage external resources like sockets and files because you can't count on the destructor to ever run.
(2) Lose determinism and then have to spend huge amounts of effort tweaking GC parameters to fix your issue, but to your point, it becomes a Jenga tower where you touch one part and the whole thing falls down again.
(3) Can easily still leak huge portions of your object graph by, for instance, throwing them into long-lived dictionaries.
and it is replaced by GC when your program behaves unexpectedly because, whoopsie, that's the one time the GC decided to run. Good luck debugging or even reproducing that.
GC usually runs on allocations, so it's quite predictable. The amount of time spent on collection is pretty much as indeterminate as the time spent on malloc/free.
And more importantly, reading it.
The main differences are that people using GC systems spend their time doing magical incantations to manage the GC wizard, and they’re a lot more smug about the goodness of their system.
I have no idea how you've come to that conclusion. For the vast majority of memory allocation in any GC'd language I can think of, you spend zero time thinking about memory management 98% of the time.
whereas in a manual language, you must consider it every time you allocate memory. That's not a bad thing, it's often dead simple in the vast majority of contexts, but still.
I've also very rarely seen code in professional code that's mean to poke or prod the GC into running.
>whereas in a manual language, you must consider it every time you allocate memory.
This is like bizarro world to me. I genuinely can't comprehend that.
Here's how memory management looks like to me, using concrete examples in languages featuring RAII like C++ or Rust:
- I have a function that needs to compute a hash so I need to allocate a hash context for it. If it's small I'll put it on the stack, otherwise it'll go on the heap. In either case when the function returns the destructor is automatically called.
- I have a function that takes the name of a file as parameter and returns its contents in a buffer. Clearly the buffer needs to be allocated on the heap, so I allocate a large enough vector or string read into it and return that. The caller will then either use it and drop it immediately or store it somewhere to be dropped later, either on its own or as part of the structure it belongs to. In either case the destructor will be called automatically and the memory will be freed.
That's easily 99.9% of what memory management looks like in the programs that I write. I have absolutely no idea what using a GC would change at any point here. Note that while this is technically "manual" memory management I never have to explicitly free anything and in the vast majority of cases I don't even have to bother implementing the destructor myself (I basically only need to implement them if I need to release external resources like, for instance, raw OpenGL handles, file descriptors and the like. The GC wouldn't help either here).
It's genuinely a non-issue as far as I'm concerned. I literally never think "uh, I have no idea when this object won't be used anymore, I wish I had a GC to figure it out". I can't even imagine when such a scenario would crop up.
- I have a function that needs to compute a hash so I need to allocate a hash context for it. At some point after the function has returned the destructor is automatically called.
- I have a function that takes the name of a file as parameter and returns its contents in a buffer. I allocate a large enough vector or string read into it and return that. The caller will then either use it or store it somewhere. In either case the destructor will be called automatically and the memory will be freed.
See how it's simpler?
You're glossing over a lot of complexity there. That's the entire point of GC, you don't have to think about when it's dropped.
Also, I wasn't arguing for the blanket necessity of GC in all contexts and for all problems.
Maybe it's just Stockholm syndrome and I'm so used to working that way that I don't even see the problem anymore but there are now a long string of replies talking abstractly about the overhead of programming in a non-GC environment and I simply don't relate at all. It's a complete non-issue as far as I'm concerned.
Wherever you're storing the reference, you have to eventually free the memory. That propagates memory-management code throughout your codebase, and is error-prone.
I totally agree that if you're allocating on the stack it's a non-issue. If you're returning a reference and always freeing in the caller, that's pretty easy too, but you have to have that logic in every single caller. If you're storing a reference on the heap somewhere, you suddenly have dynamic lifetimes with indeterminate reference counts, and it gets quite hard to 1) correctly manage memory and 2) verify that you're correctly managing memory.
The alternative is that in all three instances in a GC language, I don't have to care about memory management. Barring unusual edge cases, I can't forget to deallocate something and end up with a memory leak.
It is axiomatic that GC programs leak memory. I’ve never encountered one that didn’t. The difference is that it’s harder to see, and most programmers who have grown up with GC systems don’t know how to fix it.
”The alternative is that in all three instances in a GC language, I don't have to care about memory management.”
Again, no. The alternative is thar you aren’t paying attention, and don’t see the leaks until they become fatal. Just like cockroaches, you have them, somewhere.
30 years of experience.
”For the vast majority of memory allocation in any GC'd language I can think of, you spend zero time thinking about memory management 98% of the time.”
No, you think about 98% of the code 0% of the time. The remaining 2% ends up causing so many problems that your amortized time spent on memory management is the same.
You are missing the point. The main point behind GC is removing the complexity of writing the software. Writing your own destructors, thinking about when to free your memory or writing lifetime annotations, needing to design your app in specific way to satisfy the borrow checker etc in languages like Ada/C/C++/Rust all are additional complexity and mental overhead that is removed by GC. Your point about "just do this X and you don't need to use GC" is a reason people use GC languages, because they don't want to think about or write this "X".