(Singly) linked lists are trivial to implement in an immutable way (the article talks about the difficulty of doubly-linked lists, implemented in a mutable way).
It's trivial to have linked lists share a tail; this makes datastructures like cactus stacks really easy.
Linked lists are amenable to reasoning by induction (e.g. in Coq, Agda, Idris, etc.).
Linked lists are amenable to lazy algorithms (e.g. iterators/generators).
Linked lists can be heavily optimised, e.g. using stream fusion.
That's off the top of my head. Note that in many cases it might be preferable to use linked lists in the source, but have them compiled to some other representation like arrays (or, in the case of fusion, a single tight loop).
In the kernel, where you have to handle every single error path, this is a big deal.
* In multi-threaded context insertion and deletion can be done lock-free which is not the case for arrays ;
* For intrusive list, insertion and deletion can't fail due to memory allocation ;
* If you do only insertion at the tail and removal at the head these operation need only a pointer change which is more efficient than an array ;
* Merging two list is only one pointer operation ;
* Intrusive list have better memory allocation properties ;
* ...
The problem is that, on new hardware, linked list should be used in less cases that in the past and some people have generalized this to linked-list should never be used. This is false, if you care about performances you should keep thinking and testing what is the best data-structure in different cases. If you don't care about performances, you should use an abstraction who implement what you need and don't car about the underlying data-structure.
I just love when multithreaded code frees the element I currently iterate over in a different thread.
> For intrusive list, insertion and deletion can't fail due to memory allocation ;
As long as you store your elements on the stack or use static values you mean? Heap allocation happens at some point, you just move the location where it happens.
> If you do only insertion at the tail and removal at the head these operation need only a pointer change which is more efficient than an array
Use a circular buffer. Until the array is full you can just modify the start/end pointers.
Even if I did control it, there are probably several lists a socket might be a part of. Storing the socket in a dynamic array will only work for one of those lists. It's similar to a sparse database index - you can only have one of them. The rest of the lists have to be linked.
Not to mention, when items are shuffled around in a dynamic array, you lose the ability to have a consistent pointer to them.
on modern cpu's with huge caches, i seriously doubt this claim.
fwiw, i have played around with synthetic problems where: i insert sequence of random integers into a sorted sequence, then remove those elements one by one as determined by a random sequence of positions. and almost always, vectors outperform lists by at least couple of orders of magnitude.
or to put it another way, it is almost never about either lists / vectors or something else, and boils down to couple of 'rules' e.g. access data predictably (avoid trashing the cache), keep data compact (more cache utilization) etc. etc.
Which means that you scan the list twice for each node. First for insertion and then for deletion. Starting at maybe a hundred that would be much more efficient with a balanced search tree. They have a good Red-black tree in Linux.
But if it's only arrays vs lists - with linked lists, pointers to items are never invalidated. With dynamic arrays, they are.
Dynamic arrays are fine for plain old data arrays. But it's harder for data that has "identity" and is frequently mutated. And if a node is in multiple lists, I guess arrays are out. You'd need to store the data redundantly. Extra bad if you need atomic mutations.
So it's not surprising that linked lists perform very poorly in such circumstances.
You say "the same operation just requires pointer changes (after finding where you want to insert or delete)" like it's some trivial thing that doesn't enter the equation. But finding where you want to insert or delete in a non-contiguous linked list is not a consideration that should be an afterthought in brackets.
Furthermore, when you have found the location, it's still not _just_ pointer changes. You actually have to allocate the memory for the node, too.
Traversing pointers and allocating memory is a lot slower than working with a contiguous block of memory (assuming you don't have to re-allocate the contiguous block of memory, of course).
Either way, don't take my word for it. If you're a C++ programmer, just benchmark std::vector against std::list, or watch this video - https://youtu.be/YQs6IC-vgmo
Reallocating a big dynamic array is also a no-go in many time-constrained situations.
> You actually have to allocate the memory for the node, too.
The way this is done is by intrusive linking (the data must include list pointers). The data usually knows in which lists it is linked, so there is no point in having a version of the data without a list head.
don't forget, deletes, as well.
I'm don't know how the slab cache allocation would benchmark against allocating larger chunks, I was just trying to give a classical answer to the question.
We're talking about kernelspace, though, and different rules apply there. Memory allocation works very differently, and you have to handle every possible error path.
> Furthermore, when you have found the location, it's still not _just_ pointer changes. You actually have to allocate the memory for the node, too.
This is not normally true. In embedded development and game engine memory managers, data nodes already include list pointers, and there are several ways the data nodes can come to exist that don't involve a separate allocation per node. Sometimes it's allocations of blocks of nodes. Sometimes it's slab allocations (to use the terminology from the article) - a memory manager that pre-allocates constant sized memory blocks.
Kernel lists don't normally involve hundreds of thousands of elements, and using dynamic arrays for small lists, the separate alloc & realloc time may not be even close to amortized away.
> just benchmark std::vector against std::list
This is unconvincing! Kernel & embedded code do not normally use std::list. There are very good reasons people warn against kernel development in C++! And performance benchmarks are the lowest item on the priority & constraint list. The least bad thing that can happen is going slower. Fragmentation is a bigger priority, and dynamic arrays have much worse fragmentation patterns because the allocation size changes over time.
Also in some cases the linked list header may be embedded in other structures, so you'd have to pull the header out to go with a purely vector-based approach for when you need to shift (assuming you can't move the entire structure). And if the structure needs to reference itself in the list for quick removal, that's a problem if its index is changing. Otherwise you could just search the vector for references at linear cost.
I thought this same thing when I started doing embedded console game development and saw a lot of linked lists going on. I came to realize there are a bunch of really good reasons to use linked lists.
The biggest difference in practice is that linked list pointers are commonly fields inside the data that you're linking, as opposed to being a separate data structure. With a dynamic array, it's usually a separate data structure. Neither of those is absolute or always, but that's how it normally plays out.
With that in mind:
Sometimes you're loading a block of pre-formatted binary data off disk or from a network that has space for linked list pointers. Rather than allocate anything else, you can fill in the list pointers.
Sometimes you have a lot of small lists to manage. If you're allocating space for your list data, and the dynamic array doesn't get big enough for amortizing to take over, then you're doing double allocations, one for the data and one for the dynamic array & potentially first couple of reallocs.
Fragmentation is worse with a dynamic array (when it's a separate data structure), and re-ordering events are much costlier in arrays than with linked lists.
Consistent performance. Every insert and every delete requires the same amount of time, at the cost of a higher average traversal time. You can ameliorate some of the deletion reordering cost if you can change the order of the array, but not all use-cases allow for this.
Also, intrusively linked lists (that is, the same item represented in multiple lists) are just as poor, performance wise, when implemented with arrays.
I did a quick test of this at one point, comparing C++ std::list with a linked list; the performance of the dynamic array was significantly higher for most operations (about one order of magnitude for my test), but the worst-case was much, much worse than the linked list (somewhere close to two orders of magnitude).