Context:
Erlang programs running on heterogeneous nodes, retrieving and storing data
from Mnesia databases. These database entries are meant to be used for a long
time (e.g. across multiple Erlang version releases) remains in the form of
Erlang objects (i.e. no serialization). Among the information stored, there are
currently two uses for arrays:
Large (up to 16384 elements) arrays. Fast access to an element
using its index was the basis for choosing this type of collection.
Once the array has been created, the elements are never modified.
Small (up to 64 elements) arrays. Accesses are mostly done using indices, but there are also some iterations (foldl/foldr). Both reading and replacement of the elements is done frequently. The size of the collection remains constant.
Problem:
Erlang's documentation on arrays states that "The representation is not
documented and is subject to change without notice." Clearly, arrays should not be used in my context: database entries containing arrays may be
interpreted differently depending on the node executing the program and
unannounced changes to how arrays are implemented would make them unusable.
I have noticed that Erlang features "ordsets"/"orddict" to address a similar
issue with "sets"/"dict", and am thus looking for the "array" equivalent. Do you know of any? If none exists, my strategy is likely going to be using lists of lists to replace my large arrays, and orddict (with the index as key) to replace the smaller ones. Is there a better solution?
An array is a tuple of nested tuples and integers, with each tuple being a fixed size of 10 and representing a segment of cells. Where a segment is not currently used an integer (10) acts as a place holder. This without the abstraction is I suppose the closet equivalent.You could indeed copy the array module from otp and add to your own app and thus it would be a stable representation.
As to what you should use devoid of array depends on the data and what you will do with it. If data that would be in your array is fixed, then a tuple makes since, it has constant access time for reads/lookups. Otherwise a list sounds like a winner, be it a list of lists, list of tuples, etc. However, once again, that's a shot in the dark, because I don't know your data or how you use it.
See the implementation here: https://github.com/erlang/otp/blob/master/lib/stdlib/src/array.erl
Also see Robert Virding's answer on the implementation of array here: Arrays implementation in erlang
And what Fred Hebert says about the array in A Short Visit to Common Data Structures
An example showing the structure of an array:
1> A1 = array:new(30).
{array,30,0,undefined,100}
2> A2 = array:set(0, true, A1).
{array,30,0,undefined,
{{true,undefined,undefined,undefined,undefined,undefined,
undefined,undefined,undefined,undefined},
10,10,10,10,10,10,10,10,10,10}}
3> A3 = array:set(19, true, A2).
{array,30,0,undefined,
{{true,undefined,undefined,undefined,undefined,undefined,
undefined,undefined,undefined,undefined},
{undefined,undefined,undefined,undefined,undefined,
undefined,undefined,undefined,undefined,true},
10,10,10,10,10,10,10,10,10}}
4>
Related
I've been using Matlab on and off for decades. I thought I had a good grip on arrays, structs, cell arrays, tables, an array of structs, and a struct in which each field is an array. For the latter two, I assumed that each field needed to be of uniform type. I'm finding that no such limitation exists:
Perhaps Matlab is becoming more flexible with the years (I'm using 2015b), but it does undermine my confidence in choosing the best type of variable for a task if I find that understanding of the limitations of each type is wrong. For the purpose of this question, I can't really articulate the needs of the task because the manner in which I break down a large to-do into tasks depends on my understanding of the data types at my disposal, and their advantages/limitations.
I can (and have) read online documentation ad nauseum, and while they will walk you through code to illustrate what the data types are able to do, I haven't yet come across a succinct description of the comparative limitations between cell arrays, arrays of structs, and structs whose fields are themselves arrays -- to the point that I can use that knowledge to choose the best structure in a given situation. Basic stuff, I do find, e.g., the same field names will occur in each struct of a struct array (but as the above example shows, each field of each struct can contain highly heterogeneous data types and/or array sizes).
THE QUESTION
Can anyone point to such a comparison of limitations between cell arrays, arrays of structs, and scalar structs whose fields are themselves arrays? I'm looking for a treatment at a level that informs a coder in deciding on the best trade-off between (i) speed, (ii) memory, and (iii) readability, maintainability, and evolvability.
I've deliberately left out tables because, although I'm enamoured of their convenient access to, and subsetting of, data sets (and presentation thereof), they have proved rather slow for manipulation of data. They have their uses, and I use them liberally, but I'm not interested in them for the purpose of this comparison, which is under-the-hood algorithm coding.
I think your question eventually narrows down to these three "types" of data structures:
comparative limitations between cell arrays, arrays of structs, and structs whose fiels are themselves arrays
[Note that "structs whose fields are themselves arrays" I translate as "scalar structs" here. An array of structs can also contain arbitrary arrays. My thinking becomes clear below, I hope.]
To me, these are not very different. All three are containers for heterogeneous data. (Heterogeneous data is non-uniform data, each data element is potentially of a different type and size.) Each of these statements can return an array of any type, unrelated to the type of any other array in the container:
cell array: array{i,j}
struct array: array(i,j).value
scalar struct: array.value
So it all depends on how you want to index:
array(i,j).value
^ ^
A B
If you want to index using A only, use a cell array (though you then need curly braces, of course). If you want to index using B only, use a scalar struct. If you want both A and B, use a struct array.
There is no difference in cost that I'm aware of. Each of the arrays contained in these containers takes up some space. The spatial overhead of the various containers is similar, and I have never noted a time overhead difference.
However, there is a huge difference between these two:
array(i).value % s1
array.value(i) % s2
I think that the question deals with this difference also. s1 has a lot more spatial overhead than s2:
>> s1=struct('value',num2cell(1:100))
s1 =
1×100 struct array with fields:
value
>> s2=struct('value',1:100)
s2 =
struct with fields:
value: [1×100 double]
>> whos
Name Size Bytes Class Attributes
s1 1x100 12064 struct
s2 1x1 976 struct
The data needs 800 bytes, so s2 has 176 bytes of overhead, whereas s1 has 11264 (1408%)!
The reason is not the container, but the fact that we're storing one array with 100 elements in one, and 100 arrays with one element in the other. Each array has a header of a certain size that MATLAB uses to know what type of array it is, what sizes it has, to manage its storage and the delayed copy mechanism. The fewer arrays one has, the less memory one uses.
So, don't use a heterogeneous container to store scalars! These things only make sense when you need to store larger arrays, or arrays of different type or size.
The heterogeneous container that is not explicitly asked about (and after the edit explicitly not asked about) is the table. A table is similar to a scalar struct in that each column of the table is a single array, and different columns can have different types. Note that it is possible to use a cell array as a column, allowing for heterogenous elements to be stored in a column, but they make most sense if this is not the case.
One difference with a scalar struct is that each column must have the same number of rows. Another difference is that indexing can look like that of a cell array, a scalar struct, or a struct array.
Thus, the table forces some constrains upon the contained data, which is very beneficial in some circumstances.
However, and as the OP noted, working with tables is slower than working with structs. This is because table is a custom class, not a native type like structs and cell arrays. If you type edit table in MATLAB, you'll see the source code, how it's implemented. It's a classdef file, just like something any of us could write. Consequently, it has the same speed limitations: the JIT is not optimized for it, indexing into a table implies running a function written as an M-file, etc.
One more thing: Don't create cell arrays of structs, or scalar structs with cell arrays. This increases the levels of containers, which increases overhead (both in space and time), and makes the contents more difficult to use. I have seen questions here on SO related to difficulty accessing data, caused by this type of construct:
data{i,j}.value % A cell array with structs. Don't do this!
data.value{i,j} % A struct with cell arrays. Don't do this!
The first example is equal to a struct array (with a lot more overhead), except there is no control over the struct fields within each cell. That is, it is possible for one of the cells to not have a .value field.
The second example makes sense only if value is a different size than a second struct field. If all struct fields are (supposed to be) cell arrays of the same size like this, then use a struct array. Again, less overhead and more uniformity.
Here it says:
Arrays are useful mostly because the element indices can be computed
at run time. Among other things, this feature allows a single
iterative statement to process arbitrarily many elements of an array.
For that reason, the elements of an array data structure are required
to have the same size and should use the same data representation.
Is this still true for modern languages?
For example, Java, you can have an array of Objects or Strings, right? Each object or string can have different length. Do I misunderstand the above quote, or languages like Java implements Array differently? How?
In java all types except primitives are referenced types meaning they are a pointer to some memory location manipulated by JVM.
But there are mainly two types of programming languages, fixed-typed like Java and C++ and dynamically-typed like python and PHP. In fixed-typed languages your array should consist of the same types whether String, Object or ...
but in dynamically-typed ones there's a bit more abstraction and you can have different data types in array (I don't know the actual implementation though).
An array is a regular arrangement of data in memory. Think of an array of soldiers, all in a line, with exactly equal spacing between each man.
So they can be indexed by lookup from a base address. But all items have to be the same size. So if they are not, you store pointers or references to make them the same size. All languages use that underlying structure, except for what are sometimes called "associative arrays", indexed by key (strings usually), where you have what is called a hash table. Essentially the hash function converts the key into an array index, with a fix-up to resolve collisions.
Is there a way to create an array/slice in Go without a hard-coded array size? Why is List ignored?
In all the languages I've worked with extensively: Delphi, C#, C++, Python - Lists are very important because they can be dynamically resized, as opposed to arrays.
In Golang, there is indeed a list.Liststruct, but I see very little documentation about it - whether in Go By Example or the three Go books that I have - Summerfield, Chisnal and Balbaert - they all spend a lot of time on arrays and slices and then skip to maps. In souce code examples I also find little or no use of list.List.
It also appears that, unlike Python, Range is not supported for List - big drawback IMO. Am I missing something?
Slices are lovely, but they still need to be based on an array with a hard-coded size. That's where List comes in.
Just about always when you are thinking of a list - use a slice instead in Go. Slices are dynamically re-sized. Underlying them is a contiguous slice of memory which can change size.
They are very flexible as you'll see if you read the SliceTricks wiki page.
Here is an excerpt :-
Copy
b = make([]T, len(a))
copy(b, a) // or b = append([]T(nil), a...)
Cut
a = append(a[:i], a[j:]...)
Delete
a = append(a[:i], a[i+1:]...) // or a = a[:i+copy(a[i:], a[i+1:])]
Delete without preserving order
a[i], a = a[len(a)-1], a[:len(a)-1]
Pop
x, a = a[len(a)-1], a[:len(a)-1]
Push
a = append(a, x)
Update: Here is a link to a blog post all about slices from the go team itself, which does a good job of explaining the relationship between slices and arrays and slice internals.
I asked this question a few months ago, when I first started investigating Go. Since then, every day I have been reading about Go, and coding in Go.
Because I did not receive a clear-cut answer to this question (although I had accepted one answer) I'm now going to answer it myself, based on what I have learned, since I asked it:
Is there a way to create an array /slice in Go without a hard coded
array size?
Yes. Slices do not require a hard coded array to slice from:
var sl []int = make([]int, len, cap)
This code allocates slice sl, of size len with a capacity of cap - len and cap are variables that can be assigned at runtime.
Why is list.List ignored?
It appears the main reasons list.List seem to get little attention in Go are:
As has been explained in #Nick Craig-Wood's answer, there is
virtually nothing that can be done with lists that cannot be done
with slices, often more efficiently and with a cleaner, more
elegant syntax. For example the range construct:
for i := range sl {
sl[i] = i
}
cannot be used with list - a C style for loop is required. And in
many cases, C++ collection style syntax must be used with lists:
push_back etc.
Perhaps more importantly, list.List is not strongly typed - it is very similar to Python's lists and dictionaries, which allow for mixing various types together in the collection. This seems to run contrary
to the Go approach to things. Go is a very strongly typed language - for example, implicit type conversions never allowed in Go, even an upCast from int to int64 must be
explicit. But all the methods for list.List take empty interfaces -
anything goes.
One of the reasons that I abandoned Python and moved to Go is because
of this sort of weakness in Python's type system, although Python
claims to be "strongly typed" (IMO it isn't). Go'slist.Listseems to
be a sort of "mongrel", born of C++'s vector<T> and Python's
List(), and is perhaps a bit out of place in Go itself.
It would not surprise me if at some point in the not too distant future, we find list.List deprecated in Go, although perhaps it will remain, to accommodate those rare situations where, even using good design practices, a problem can best be solved with a collection that holds various types. Or perhaps it's there to provide a "bridge" for C family developers to get comfortable with Go before they learn the nuances of slices, which are unique to Go, AFAIK. (In some respects slices seem similar to stream classes in C++ or Delphi, but not entirely.)
Although coming from a Delphi/C++/Python background, in my initial exposure to Go I found list.List to be more familiar than Go's slices, as I have become more comfortable with Go, I have gone back and changed all my lists to slices. I haven't found anything yet that slice and/or map do not allow me to do, such that I need to use list.List.
I think that's because there's not much to say about them as the container/list package is rather self-explanatory once you absorbed what is the chief Go idiom for working with generic data.
In Delphi (without generics) or in C you would store pointers or TObjects in the list, and then cast them back to their real types when obtaining from the list. In C++ STL lists are templates and hence parameterized by type, and in C# (these days) lists are generic.
In Go, container/list stores values of type interface{} which is a special type capable to represent values of any other (real) type—by storing a pair of pointers: one to the type info of the contained value, and a pointer to the value (or the value directly, if it's size is no greater than the size of a pointer). So when you want to add an element to the list, you just do that as function parameters of type interface{} accept values coo any type. But when you extract values from the list, and what to work with their real types you have to either type-asert them or do a type switch on them—both approaches are just different ways to do essentially the same thing.
Here is an example taken from here:
package main
import ("fmt" ; "container/list")
func main() {
var x list.List
x.PushBack(1)
x.PushBack(2)
x.PushBack(3)
for e := x.Front(); e != nil; e=e.Next() {
fmt.Println(e.Value.(int))
}
}
Here we obtain an element's value using e.Value() and then type-assert it as int a type of the original inserted value.
You can read up on type assertions and type switches in "Effective Go" or any other introduction book. The container/list package's documentation summaries all the methods lists support.
Note that Go slices can be expanded via the append() builtin function. While this will sometimes require making a copy of the backing array, it won't happen every time, since Go will over-size the new array giving it a larger capacity than the reported length. This means that a subsequent append operation can be completed without another data copy.
While you do end up with more data copies than with equivalent code implemented with linked lists, you remove the need to allocate elements in the list individually and the need to update the Next pointers. For many uses the array based implementation provides better or good enough performance, so that is what is emphasised in the language. Interestingly, Python's standard list type is also array backed and has similar performance characteristics when appending values.
That said, there are cases where linked lists are a better choice (e.g. when you need to insert or remove elements from the start/middle of a long list), and that is why a standard library implementation is provided. I guess they didn't add any special language features to work with them because these cases are less common than those where slices are used.
From: https://groups.google.com/forum/#!msg/golang-nuts/mPKCoYNwsoU/tLefhE7tQjMJ
It depends a lot on the number of elements in your lists,
whether a true list or a slice will be more efficient
when you need to do many deletions in the 'middle' of the list.
#1
The more elements, the less attractive a slice becomes.
#2
When the ordering of the elements isn't important,
it is most efficient to use a slice and
deleting an element by replacing it by the last element in the slice and
reslicing the slice to shrink the len by 1
(as explained in the SliceTricks wiki)
So
use slice
1. If order of elements in list is Not important, and you need to delete, just
use List swap the element to delete with last element, & re-slice to (length-1)
2. when elements are more (whatever more means)
There are ways to mitigate the deletion problem --
e.g. the swap trick you mentioned or
just marking the elements as logically deleted.
But it's impossible to mitigate the problem of slowness of walking linked lists.
So
use slice
1. If you need speed in traversal
Unless the slice is updated way too often (delete, add elements at random locations) the memory contiguity of slices will offer excellent cache hit ratio compared to linked lists.
Scott Meyer's talk on the importance of cache..
https://www.youtube.com/watch?v=WDIkqP4JbkE
list.List is implemented as a doubly linked list. Array-based lists (vectors in C++, or slices in golang) are better choice than linked lists in most conditions if you don't frequently insert into the middle of the list. The amortized time complexity for append is O(1) for both array list and linked list even though array list has to extend the capacity and copy over existing values. Array lists have faster random access, smaller memory footprint, and more importantly friendly to garbage collector because of no pointers inside the data structure.
Is there any tricky way to implement a set data structure (a collection of unique values) in C? All elements in a set will be of the same type and there is a huge RAM memory.
As I know, for integers it can be done really fast'N'easy using value-indexed arrays. But I'd like to have a very general Set data type. And it would be nice if a set could include itself.
There are multiple ways of implementing set (and map) functionality, for example:
tree-based approach (ordered traversal)
hash-based approach (unordered traversal)
Since you mentioned value-indexed arrays, let's try the hash-based approach which builds naturally on top of the value-indexed array technique.
Beware of the advantages and disadvantages of hash-based vs. tree-based approaches.
You can design a hash-set (a special case of hash-tables) of pointers to hashable PODs, with chaining, internally represented as a fixed-size array of buckets of hashables, where:
all hashables in a bucket have the same hash value
a bucket can be implemented as a dynamic array or linked list of hashables
a hashable's hash value is used to index into the array of buckets (hash-value-indexed array)
one or more of the hashables contained in the hash-set could be (a pointer to) another hash-set, or even to the hash-set itself (i.e. self-inclusion is possible)
With large amounts of memory at your disposal, you can size your array of buckets generously and, in combination with a good hash method, drastically reduce the probability of collision, achieving virtually constant-time performance.
You would have to implement:
the hash function for the type being hashed
an equality function for the type being used to test whether two hashables are equal or not
the hash-set contains/insert/remove functionality.
You can also use open addressing as an alternative to maintaining and managing buckets.
Sets are usually implemented as some variety of a binary tree. Red black trees have good worst case performance.
These can also be used to build an map to allow key / value lookups.
This approach requires some sort of ordering on the elements of the set and the key values in a map.
I'm not sure how you would manage a set that could possibly contain itself using binary trees if you limit set membership to well defined types in C ... comparison between such constructs could be problematic. You could do it easily enough in C++, though.
The way to get genericity in C is by void *, so you're going to be using pointers anyway, and pointers to different objects are unique. This means you need a hash map or binary tree containing pointers, and this will work for all data objects.
The downside of this is that you can't enter rvalues independently. You can't have a set containing the value 5; you have to assign 5 to a variable, which means it won't match a random 5. You could enter it as (void *) 5, and for practical purposes this is likely to work with small integers, but if your integers can get into large enough sizes to compete with pointers this has a very small probability of failing.
Nor does this work with string values. Given char a[] = "Hello, World!"; char b[] = "Hello, World!";, a set of pointers would find a and b to be different. You would probably want to hash the values, but if you're concerned about hash collisions you should save the string in the set and do a strncmp() to compare the stored string with the probing string.
(There's similar problems with floating-point numbers, but trying to represent floating-point numbers in sets is a bad idea in the first place.)
Therefore, you'd probably want a tagged value, one tag for any sort of object, one for integer value, and one for string value, and possibly more for different sorts of values. It's complicated, but doable.
If the maximum number of elements in the set (the cardinality of the underlying data type) is small enough, you might want to consider using a plain old array of bits (or whatever you call them in your favourite language).
Then you have a simple set membership check: bit n is 1 if element n is in the set. You could even count 'ordinary' members from 1, and only make bit 0 equal to 1 if the set contains itself.
This approach will probably require some sort of other data structure (or function) to translate from the member data type to the position in the bit array (and back), but it makes basic set operations (union, intersection, membership test, difference, insertion, removal,compelment) very very easy. And it is only suitable for relatively small sets, you wouldn't want to use it for sets of 32-bit integers I don't suppose.
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Possible Duplicate:
Arrays, What’s the point?
I tried to ask this question before in What is the difference between an array and a list? but my question was closed before reaching a conclusive answer (more about that).
I'm trying to understand what is really meant by the word "array" in computer science. I am trying to reach an answer not have a discussion as per the spirit of this website. What I'm asking is language agnostic but you may draw on your knowledge of what arrays are/do in various languages that you've used.
Ways of thinking about this question:
Imagine you're designing a new programming language and you decide to implement arrays in it; what does that mean they do? What will the properties and capabilities of those things be. If it depends on the type of language, how so?
What makes an array an array?
When is an array not an array? When it is, for example, a list, vector, table, map, or collection?
It's possible there isn't one precise definition of what an array is, if that is the case then are there any standard or near-standard assumptions or what an array is? Are there any common areas at least? Maybe there are several definitions, if that is the case I'm looking for the most precision in each of them.
Language examples:
(Correct me if I'm wrong on any of these).
C arrays are contiguous blocks of memory of a single type that can be traversed using pointer arithmetic or accessed at a specific offset point. They have a fixed size.
Arrays in JavaScript, Ruby, and PHP, have a variable size and can store an object/scalar of any type they can also grow or have elements removed from them.
PHP arrays come in two types: numeric and associative. Associative arrays have elements that are stored and retrieved with string keys. Numeric arrays have elements that are stored and retrieved with integers. Interestingly if you have: $eg = array('a', 'b', 'c') and you unset($eg[1]) you still retrieve 'c' with $eg[2], only now $eg[1] is undefined. (You can call array_values() to re-index the array). You can also mix string and integer keys.
At this stage of sort of suspecting that C arrays are the only true array here and that strictly-speaking for an array to be an array it has to have all the characteristics I mention in that first bullet point. If that's the case then — again these are suspicions that I'm looking to have confirmed or rejected — arrays in JS and Ruby are actually vectors, and PHP arrays are probably tables of some kind.
Final note: I've made this community wiki so if answers need to be edited a few times in lieu of comments, go ahead and do that. Consensus is in order here.
It is, or should be, all about abstraction
There is actually a good question hidden in there, a really good one, and it brings up a language pet peeve I have had for a long time.
And it's getting worse, not better.
OK: there is something lowly and widely disrespected Fortran got right that my favorite languages like Ruby still get wrong: they use different syntax for function calls, arrays, and attributes. Exactly how abstract is that? In fortran function(1) has the same syntax as array(1), so you can change one to the other without altering the program. (I know, not for assignments, and in the case of Fortran it was probably an accident of goofy punch card character sets and not anything deliberate.)
The point is, I'm really not sure that x.y, x[y], and x(y) should have different syntax. What is the benefit of attaching a particular abstraction to a specific syntax? To make more jobs for IDE programmers working on refactoring transformations?
Having said all that, it's easy to define array. In its first normal form, it's a contiguous sequence of elements in memory accessed via a numeric offset and using a language-specific syntax. In higher normal forms it is an attribute of an object that responds to a typically-numeric message.
array |əˈrā|
noun
1 an impressive display or range of a particular type of thing : there is a vast array of literature on the topic | a bewildering array of choices.
2 an ordered arrangement, in particular
an arrangement of troops.
Mathematics: an arrangement of quantities or symbols in rows and columns; a matrix.
Computing: an ordered set of related elements.
Law: a list of jurors empaneled.
3 poetic/literary elaborate or beautiful clothing : he was clothed in fine array.
verb
[ trans. ] (usu. be arrayed) display or arrange (things) in a particular way : arrayed across the table was a buffet | the forces arrayed against him.
[ trans. ] (usu. be arrayed in) dress someone in (the clothes specified) : they were arrayed in Hungarian national dress.
[ trans. ] Law empanel (a jury).
ORIGIN Middle English (in the senses [preparedness] and [place in readiness] ): from Old French arei (noun), areer (verb), based on Latin ad- ‘toward’ + a Germanic base meaning ‘prepare.’
From FOLDOC:
array
1. <programming> A collection of identically typed data items
distinguished by their indices (or "subscripts"). The number
of dimensions an array can have depends on the language but is
usually unlimited.
An array is a kind of aggregate data type. A single
ordinary variable (a "scalar") could be considered as a
zero-dimensional array. A one-dimensional array is also known
as a "vector".
A reference to an array element is written something like
A[i,j,k] where A is the array name and i, j and k are the
indices. The C language is peculiar in that each index is
written in separate brackets, e.g. A[i][j][k]. This expresses
the fact that, in C, an N-dimensional array is actually a
vector, each of whose elements is an N-1 dimensional array.
Elements of an array are usually stored contiguously.
Languages differ as to whether the leftmost or rightmost index
varies most rapidly, i.e. whether each row is stored
contiguously or each column (for a 2D array).
Arrays are appropriate for storing data which must be accessed
in an unpredictable order, in contrast to lists which are
best when accessed sequentially. Array indices are
integers, usually natural numbers, whereas the elements of
an associative array are identified by strings.
2. <architecture> A processor array, not to be confused with
an array processor.
Also note that in some languages, when they say "array" they actually mean "associative array":
associative array
<programming> (Or "hash", "map", "dictionary") An array
where the indices are not just integers but may be
arbitrary strings.
awk and its descendants (e.g. Perl) have associative
arrays which are implemented using hash coding for faster
look-up.
If you ignore how programming languages model arrays and lists, and ignore the implementation details (and consequent performance characteristics) of the abstractions, then the concepts of array and list are indistinguishable.
If you introduce implementation details (still independent of programming language) you can compare data structures like linked lists, array lists, regular arrays, sparse arrays and so on. But then you are not longer comparing arrays and lists per se.
The way I see it, you can only talk about a distinction between arrays and lists in the context of a programming language. And of course you are then talking about arrays and lists as supported by that language. You cannot generalize to any other language.
In short, I think this question is based on a false premise, and has no useful answer.
EDIT: in response to Ollie's comments:
I'm not saying that it is not useful to use the words "array" and "list". What I'm saying is the words do not and cannot have precise and distinct definitions ... except in the context of a specific programming language. While you would like the two words to have distinct meaning, it is a fact that they don't. Just take a look at the way the words are actually used. Furthermore, trying to impose a new set of definitions on the world is doomed to fail.
My point about implementation is that when we compare and contrast the different implementations of arrays and lists, we are doing just that. I'm not saying that it is not a useful thing to do. What I am saying is that when we compare and contrast the various implementations we should not get all hung up about whether we call them arrays or lists or whatever. Rather we should use terms that we can agree on ... or not use terms at all.
To me, "array" means "ordered collection of things that is probably efficiently indexable" and "list" means "ordered collection of things that may be efficiently indexable". But there are examples of both arrays and lists that go against the trend; e.g. PHP arrays on the one hand, and Java ArrayLists on the other hand. So if I want to be precise ... in a language-agnostic context, I have to talk about "C-like arrays" or "linked lists" or some other terminology that makes it clear what data structure I really mean. The terms "array" and "list" are of no use if I want to be clear.
An array is an ordered collection of data items indexed by integer. It is not possible to be certain of anything more. Vote for this answer you believe this is the only reasonable outcome of this question.
An array:
is a finite collection of elements
the elements are ordered, and this is their only structure
elements of the same type
supported efficient random access
has no expectation of efficient insertions
may or may not support append
(1) differentiates arrays from things like iterators or generators. (2) differentiates arrays from sets. (3) differentiates arrays from things like tuples where you get an int and a string. (4) differentiates arrays from other types of lists. Maybe it's not always true, but a programmer's expectation is that random access is constant time. (5) and (6) are just there to deny additional requirements.
I would argue that a real array stores values in contiguous memory. Anything else is only called an array because it can be used like array, but they aren't really ("arrays" in PHP are definately not actual arrays (non-associative)). Vectors and such are extensions of arrays, adding additional functionality.
an array is a container, and the objects it holds have no any relationships except the order; the objects are stored in a continuous space abstractly (high level, of course low level may continuous too), so you could access them by slot[x,y,z...].
for example, per array[2,3,5,7,1], you could get 5 using slot[2] (slot[3] in some languages).
for a list, a container too, each object (well, each object-holder exactly such as slot or node) it holds has indicators which "point" to other object(s) and this is the main relationship; in general both high or low level the space is not continuous, but may be continuous; so accessing by slot[x,y,z...] is not recommended.
for example, per |-2-3-5-7-1-|, you need to do a travel from first object to 3rd one to get 5.