Want function programming and purity? Check.
Want C style/low abstraction code? Check.
Want extreme C++ metaprogramming? Check.
Want C#'s LINQ? Check.
Want an improved version of C++'s STL? Check.
Want low cognitive load memory management through a GC? Check.
Want highly tailored memory management? Check.
Want high level object oriented abstractions? Check.
Want memory safety? Check.
Want systems programming? Check.
Want rapid prototyping? Check.
D, fundamentally, assumes the programmer knows what approach they should take and lets them do it. There are no "we know better" design decisions in the language. I think this might be because D is so community driven. With no real company backing D was left in the hands of enthusiasts coming from all sorts of different backgrounds to implement ideas they liked.
That's a major problem, and not a feature.
One of C++'s main drawbacks is its size and arcane features, to the point that the language is known for being impossible to master. If all D brings to the table is an agenda to pick off C++'s complexity and drive it up even further then I fail to see what problems that will solve while it creates many others.
auto names = [ "Burke", "Connor", "Frank", "Everett", "Albert", "George", "Harris", "David"];
names.filter!(a => a.length == 5)
.array // convert from lazy range to array so we can sort
.sort!()
.map!(a => a.asUpperCase)
.joiner("\n")
.writeln;
Ranges enable lazy processing with efficient static dispatch against arbitrary types of ranges. Those individual algorithm functions are basically all template functions that return types tailored to match the input which allows the lazy evaluation to work. When writeln asks for the first element to print it asks joiner which asks map which asks asUpperCase and so on. The results are calculated upon request, not in advance, which helps you forgo a lot of memory allocations for storing temporary results.UFCS lets you call a function as if it were a member of the first parameter (i.e. fun(x, y) -> x.fun(y)). This lets you write it as if it were chain rather than a series of inside out function calls (i.e. `writeln(joiner(map!(a => asUpperCase(a)(sort!()(array(filter!(a => a.length == 5)(names)))), "\n"))`).
There is exactly two memory allocations in all of that. Once for the initial array and again prior to sorting because it's not reasonable to sort a lazy range. We could have reused the initial array by eagerly removing the items being filtered from it if we wanted.
And built in at the compiler level, so it happens when you compile your program as you normally would, the tests show up while compiling, and the output does not contain the code. Always impressed me.
And yes, templates are so much better in D than in C++ or in C# :)
How does @nogc work in D? Is it easy to keep track of what needs freeing and what does not or is it easy to mix up and get hard bugs? Also, what do these bugs look like? Is use-after-free possible or how is the failure mode i that case? Is it possible to call free on an object after it's been garbage collected?
The answer to all of your questions is basically the same as they are in C and C++. D does have @safe though which prevents unsafe memory operations and Walter is in the process of ratcheting up the memory safety with DIP1000[2].
1. https://dlang.org/phobos/std_experimental_allocator.html 2. https://github.com/dlang/DIPs/blob/master/DIPs/DIP1000.md
So it is up to the community if they want to accept such change.
I should note that they still need some help cleaning the standard library and compiler corner cases in regard to @safe.
As always in such cases, to validate binary libraries, they need some kind of metadata to indicate they are safe libraries (aka they only use of @safe or @thrusted code).
.NET does this with MSIL metadata, Modula-3 does it directly on the module definition section, for example.
GC + range checks provide memory safety to most programs without the kind of extra work you need in Rust. This is a big reason why they are so common in industry.
@safe:
at the top of your code, it'll be memory safe (excluding issues which we plug 'em when we find 'em). I wouldn't say that makes it fundamentally different from Rust. What is fundamentally different from Rust is the approach D uses to implement memory safety.The next option is to use reference counting by wrapping your data in Rc/Arc (depending on whether you need atomicity or not).
But that can still leak memory if you have cyclic data structures and can't break the cycle with Weak pointers.
At this point, what you need is a garbage collector.