> Sorry, but where did you got this definition from?
It is from experience with object oriented languages (mainly C++ and Java). Technically, you can do everything manually, but that involves shoehorning things into the OO paradigm that do not naturally fit, like the article author did when he claimed struct file_operations was a vtable when it has ->check_flags(), which would be equivalent to a static member function in C++. That is never in a vtable.
If Al Viro were trying to restrict himself to object oriented programming, he would need to remove function pointers to what are effectively the equivalent of static member functions in C++ to turn it into a proper vtable, and handle accesses to that function through the “class”, rather than the “object”.
Of course, since he is not doing object oriented programming, placing pointers to what would be virtual member functions and static member functions into the same structure is fine. There will never be a use case where you want to inherit from a filesystem implementation’s struct file_operations, so there is no need for the decoupling that object oriented programming forces.
> I've always thought OOP as a way of organizing your data and your code, sometimes supported by language-specific constructs, but not necessarily.
It certainly can be, but it is not the only way.
> Can you organize your data into lists, trees, and hashmaps even if your language does not have those as native types?
This is an odd question. First, exactly what is a native type? If you mean primitive types, then yes. Even C++ does that. If you mean standard library compound types, again, yes. The C++ STL started as a third party library at SGI before becoming part of the C++ standard. If you mean types that you can define, then probably not without a bunch of pain, as then we are going back to the dark days of manually remembering offsets as people had to do in assembly language, although it is technically possible to do in both C and C++.
What you are asking seems to be exactly what data abstraction is, which involves making an interface that separates use and implementation, allowing different data structures to be used to organize data using the same interface. As per Wikipedia:
> For example, one could define an abstract data type called lookup table which uniquely associates keys with values, and in which values may be retrieved by specifying their corresponding keys. Such a lookup table may be implemented in various ways: as a hash table, a binary search tree, or even a simple linear list of (key:value) pairs. As far as client code is concerned, the abstract properties of the type are the same in each case.
https://en.wikipedia.org/wiki/Abstraction_(computer_science)...
Getting back to doing data structures without object oriented programming, this is often done in C using a structure definition and the CPP (C PreProcessor) via intrusive data structures. Those break encapsulation, but are great for performance since they can coalesce memory allocations and reduce pointer indirections for objects indexed by multiple structures. They also are extremely beneficial for debugging, since you can see all data structures indexing the object. Here are some of the more common examples:
https://github.com/openbsd/src/blob/master/sys/sys/queue.h
https://github.com/openbsd/src/blob/master/sys/sys/tree.h
sys/queue.h is actually part of the POSIX standard, while sys/tree.h never achieved standardization. You will find a number of libraries that implement trees like libuutil on Solaris/Illumos, glib on GNU, sys/tree.h on BSD, and others. The implementations are portable to other platforms, so you can pick the one you want and use it.
As for “hash maps” or hash tables, those tend to be more purpose built in practice to fit the data from what I have seen. However, generic implementations exist:
https://stackoverflow.com/questions/6118539/why-are-there-no...
That said, anyone using hash tables at scale should pay very close attention to how their hash function distributes keys to ensure it is as close to uniformly random as possible, or you are going to have a bad time. Most other applications would be fine using binary search trees. It probably is not a good idea to use hash tables with user controlled keys from a security perspective, since then a guy named Bob can pick keys that cause collisions to slow everything down in a DoS attack. An upgrade from binary search trees that does not risk issues from hash function collisions would be B-trees.
By the way, B-trees are containers and cannot function as intrusive data structures, so you give up some convenience when debugging if you use B-Trees.