Shadowing and garbage collecting in F# - f#

This is my first time encountering shadowing and there don't seem to be resources specific to my question.
If I do the following
let x = a list
let x = another list
Then x will hold the contents of the second list.
I assume (based on what my instructor said) that the first list is not automatically destroyed and simply garbage collected at the end of the scope.
My question is why?
Why do we not automatically get rid of the first list once the immutable is shadowed? It would lead me to think that the data can still somehow be accessed. If so, how?

Assuming x was the only reference to "a list", then yes, in your code example, "a list" becomes eligible for garbage collection.
Being eligible for garbage collection doesn't however mean that the object is reclaimed at any particular point in the code, particularly not "at the end of the scope". The idea that things get cleaned up at the end of scopes is related to destructors in C++*, GC doesn't work like that at all in .NET. The GC runs concurrently and may or may not reclaim anything eligible at any point in time. That may happen even before the code exits the current scope, or later, or never. The GC doesn't even care if you have a variable in scope that refers to an object, if you're not using it, it doesn't count (see liveness analysis).
*There's a similar mechanism in F#, though: see use bindings.

Consider the following:
let x = list1
let y = x
let x = list2
Now even though you are shadowing x, you can still access list1. This is just one example -- in general, it's not possible to statically identify all references (aliases) to a particular value. Instead the garbage collector identifies them at runtime.
Obviously in this specific case you might suggest that having some special support would make sense, and indeed perhaps there is -- I don't know myself.

Related

Do eager pipes create multiple lists in F#?

When using a list an pipes does it create mutliple intermediate lists? If so is this not very bad for garbage collection?
let mylist = [...]
let filterByPipes ls =
somefilter ls //is a list created here
|> otherFiler // and then again here
|> filtersForDays // and finally returned here
Yes, F# uses applicative evaluation order, which means that every value has to be fully evaluated before it can be passed as parameter to a function, which means that yes, at every step a new list is created.
As to whether it's bad for garbage collection... "First measure then optimize" - the first rule of optimization.
In most circumstances, the amount of data is so miniscule, it doesn't really make any difference, definitely not enough to make up for the massive gain in code readability.
But if your measurements do determine a bottleneck in this particular place, and it turns out to be significant for the end goal, - then yes, you'll have to manually fuse the processing chain. Or perhaps employ a more efficient data structure. It all would depend on what the optimization goal is.

Garbage collection and the memoization of a string-to-string function

The following exercise comes from p. 234 of Ierusalimschy's Programming in Lua (4th edition). (NB: Earlier in the book, the author explicitly rejects the word memoization, and insists on using memorization instead. Keep this in mind as you read the excerpt below.)
Exercise 23.3: Imagine you have to implement a memorizing table for a function from strings to strings. Making the table weak will not do the removal of entries, because weak tables do not consider strings as collectable objects. How can you implement memorization in that case?
I am stumped!
Part of my problem is that I have not been able to devise a way to bring about the (garbage) collection of a string.
In contrast, with a table, I can equip it with finalizer that will report when the table is about to be collected. Is there a way to confirm that a given string (and only that string) has been garbage-collected?
Another difficulty is simply figuring out what the desired function's specification is. The best I can do is to figure out what it isn't. Earlier in the book (p. 225), the author gave the following example of a "memorizing" function:
Imagine a generic server that takes requests in the form of strings with Lua code. Each time it gets a request, it runs load on the string, and then calls the resulting function. However, load is an expensive function, and some commands to the server may be quite frequent. Instead of calling load repeatedly each time it receives a common command like "closeconnection()", the server can memorize the results from load using an auxiliary table. Before calling load, the server checks in the table whether the given string already has a translation. If it cannot find a match then (and only then) the server calls load and stores the result into the table. We can pack this behavior in a new function:
[standard memo(r)ized implementation omitted; see variant using a weak-value table below]
The savings with this scheme can be huge. However, it may also cause unsuspected waste. ALthough some commands epeat over and over, many other commands happen only once. Gradually, the ["memorizing"] table results accumulates all commands the server has ever received plus their respective codes; after enough time, this behavior will exhaust the server's memory.
A weak table provides a simple solution to this problem. If the results table has weak values, each garbage-collection cycle will remove all translations not in use at that moment (which means virtually all of them)1:
local results = {}
setmetatable(results, {__mode = "v"}) -- make values weak
function mem_loadstring (s)
local res = results[s]
if res == nil then -- results not available?
res = assert(load(s)) -- compute new results
result[s] = res -- save for later reuse
end
return res
end
As the original problem statement notes, this scheme won't work when the function to be memo(r)ized returns strings, because the garbage collector does not treat strings as "collectable".
Of course, if one is allowed to change the desired function's interface so that instead of returning a string, it returns a singleton table whose sole item is the real result string, then the problem becomes almost trivial, but I find it hard to believe that the author had such a crude "solution" in mind2.
In case it matters, I am using Lua 5.3.
1 As an aside, if the rationale for memo(r)ization is to avoid invoking load more often than necessary, the scheme proposed by the author does not make sense to me. It seems to me that this scheme is based on the assumption (a heuristic, really) that a translation that is used frequently, and thus would pay to memo(r)ize, is also one that is always reachable (and hence not collectable). I don't see why this should necessarily, or even likely, be the case.
2 One may be able to put lipstick on this pig in the form of a __tostring method that would allow the table (the one returned by the memo(r)ized function) to masquerade as a string in certain contexts; it's still a pig, though.
Your idea is correct: wrap string into a table (because table is collectable).
function memormoize (func_from_string_to_string)
local cached = {}
setmetatable(cached, {__mode = "v"})
return
function(s)
local c = cached[s] or {func_from_string_to_string(s)}
cached[s] = c
return c[1]
end
end
And I see no pigs in this solution :-)
one that is always reachable (and hence not collectable). I don't see why this should necessarily, or even likely, be the case.
There will be no "always reachable" items in a weak table.
But most frequent items will be recalculated only once per GC cycle.
The ideal solution (never collect frequently used items) would require more complex implementation.
For example, you can move items from normal cache to weak cache when item's "inactivity timer" reaches some threshold.

How to detect "dangling pointers" if "Assigned()" can't do it?

In another question, I found out that the Assigned() function is identical to Pointer <> nil. It has always been my understanding that Assigned() was detecting these dangling pointers, but now I've learned it does not. Dangling Pointers are those which may have been created at one point, but have since been free'd and haven't been assigned to nil yet.
If Assigned() can't detect dangling pointers, then what can? I'd like to check my object to make sure it's really a valid created object before I try to work with it. I don't use FreeAndNil as many recommend, because I like to be direct. I just use SomeObject.Free.
Access Violations are my worst enemy - I do all I can to prevent their appearance.
If you have an object variable in scope and it may or may not be a valid reference, FreeAndNil is what you should be using. That or fixing your code so that your object references are more tightly managed so it's never a question.
Access Violations shouldn't be thought of as an enemy. They're bugs: they mean you made a mistake that needs fixed. (Or that there's a bug in some code you're relying on, but I find most often that I'm the one who screwed up, especially when dealing with the RTL, VCL, or Win32 API.)
It is sometimes possible to detect when the address a pointer points to resides in a memory block that is on the heap's list of freed memory blocks. However, this requires comparing the pointer to potentially every block in the heap's free list which could contain thousands of blocks. So, this is potentially a computationally intensive operation and something you would not want to do frequently except perhaps in a severe diagnostic mode.
This technique only works while the memory block that the pointer used to point to continues to sit in the heap free list. As new objects are allocated from the heap, it is likely that the freed memory block will be removed from the heap free list and put back into active play as the home of a new, different object. The original dangling pointer still points to the same address, but the object living at that address has changed. If the newly allocated object is of the same (or compatible) type as the original object now freed, there is practically no way to know that the pointer originated as a reference to the previous object. In fact, in this very special and rare situation, the dangling pointer will actually work perfectly well. The only observable problem might be if someone notices that the data has changed out from under the pointer unexpectedly.
Unless you are allocating and freeing the same object types over and over again in rapid succession, chances are slim that the new object allocated from that freed memory block will be the same type as the original. When the types of the original and the new object are different, you have a chance of figuring out that the content has changed out from under the pointer. However, to do that you need a way to know the type of the original object that the pointer referred to. In many situations in native compiled applications, the type of the pointer variable itself is not retained at runtime. A pointer is a pointer as far as the CPU is concerned - the hardware knows very little of data types. In a severe diagnostic mode it's conceivable that you could build a lookup table to associate every pointer variable with the type allocated and assigned to it, but this is an enormous task.
That's why Assigned() is not an assertion that the pointer is valid. It just tests that the pointer is not nil.
Why did Borland create the Assigned() function to begin with? To further hide pointerisms from novice and occasional programmers. Function calls are easier to read and understand than pointer operations.
The bottom line is that you should not be attempting to detect dangling pointers in code. If you are going to refer to pointers after they have been freed, set the pointer to nil when you free it. But the best approach is not to refer to pointers after they have been freed.
So, how do you avoid referring to pointers after they have been freed? There are a couple of common idioms that get you a long way.
Create objects in a constructor and destroy them in the destructor. Then you simply cannot refer to the pointer before creation or after destruction.
Use a local variable pointer that is created at the beginning of the function and destroyed as the last act of the function.
One thing I would strongly recommend is to avoid writing if Assigned() tests into your code unless it is expected behaviour that the pointer may not be created. Your code will become hard to read and you will also lose track of whether the pointer being nil is to be expected or is a bug.
Of course we all do make mistakes and leave dangling pointers. Using FreeAndNil is one cheap way to ensure that dangling pointer access is detected. A more effective method is to use FastMM in full debug mode. I cannot recommend this highly enough. If you are not using this wonderful tool, you should start doing so ASAP.
If you find yourself struggling with dangling pointers and you find it hard to work out why then you probably need to refactor the code to fit into one of the two idioms above.
You can draw a parallel with array indexing errors. My advice is not to check in code for validity of index. Instead use range checking and let the tools do the work and keep the code clean. The exception to this is where the input comes from outside your program, e.g. user input.
My parting shot: only ever write if Assigned if it is normal behaviour for the pointer to be nil.
Use a memory manager, such as FastMM, that provides debugging support, in particular to fill a block of freed memory with a given byte pattern. You can then dereference the pointer to see if it points at a memory block that starts with the byte pattern, or you can let the code run normallly ad raise an AV if it tries to access a freed memory block through a dangling pointer. The AV's reported memory address will usually be either exactly as, or close to, the byte pattern.
Nothing can find a dangling (once valid but then not) pointer. It's your responsibility to either make sure it's set to nil when you free it's content, or to limit the scope of the pointer variable to only be available within the scope it's valid. (The second is the better solution whenever possible.)
The core point is that the way how objects are implemented in Delphi has some built-in design drawbacks:
there is no distinction between an object and a reference to an object. For "normal" variables, say a scalar (like int) or a record, these two use cases can be well told apart - there's either a type Integer or TSomeRec, or a type like PInteger = ^Integer or PSomeRec = ^TSomeRec, which are different types. This may sound like a neglectable technicality, but it isn't: a SomeRec: TSomeRec denotes "this scope is the original owner of that record and controls its lifecycle", while SomeRec: PSomeRec tells "this scope uses a transient reference to some data, but has no control over the record's lifecycle. So, as dumb it may sound, for objects there's virtually no one who has denotedly control over other objects' lifecycles. The result is - surprise - that the lifecycle state of objects may in certain situations be unclear.
an object reference is just a simple pointer. Basically, that's ok, but the problem is that there's sure a lot of code out there which treats object references as if they were a 32bit or 64bit integer number. So if e.g. Embarcadero wanted to change the implementation of an object reference (and make it not a simple pointer any more), they would break a lot of code.
But if Embarcadero wanted to eliminate dangling object pointers, they would have to redesign Delphi object references:
when an object is freed, all references to it must be freed, too. This is only possible by double-linking both, i.e. the object instance must carry a list with all of the references to it, that is, all memory addresses where such pointers are (on the lowest level). Upon destruction, that list is traversed, and all those pointers are set to nil
a little more comfortable solution were that the "one" holding such a reference can register a callback to get informed when a referenced object is destroyed. In code: when I have a reference FSomeObject: TSomeObject I would want to be able to write in e.g. SetSomeObject: FSomeObject.OnDestruction := Self.HandleDestructionOfSomeObject. But then FSomeObject can't be a pointer; instead, it would have to be at least an (advanced) record type
Of course I can implement all that by myself, but that is tedious, and isn't it something that should be addressed by the language itself? They also managed to implement for x in ...

Does erlang implement record copy-and-modify in any clever way?

given:
-record(foo, {a, b, c}).
I do something like this:
Thing = #foo{a={1,2}, b={3,4}, c={5,6}},
Thing1 = Thing#foo{a={7,8}}.
From a semantic view, Thing and Thing1 are unique entities. However, from a language implementation standpoint, making a full copy of Thing to generate Thing1 would be intensely wasteful. For example, if the record were a megabyte in size and I made a thousand "copies," each modifying a couple of bytes, I've just burned a gigabyte. If the internal structure kept track of a representation of the parent structure and each derivative marked up that parent in a way that indicated its own change but preserved everyone elses' versions, the derivates could be created with a minimum of memory overhead.
My question is this: is erlang doing anything clever - internally - to keep the overhead of the usual erlang scribble;
Thing = #ridiculously_large_record,
Thing1 = make_modified_copy(Thing),
Thing2 = make_modified_copy(Thing1),
Thing3 = make_modified_copy(Thing2),
Thing4 = make_modified_copy(Thing3),
Thing5 = make_modified_copy(Thing4)
...to a minimum?
I ask because there would be a number of changes to the way that I did cross-process communications if this were the case.
The exact workings of the garbage collection and memory allocation is only known to a few. Thankfully, they are very happy to share their knowledge and the following is based on what I have learnt from the erlang-questions mailing list and by discussing with OTP developers.
When messaging between processes, the content is always copied as there is no shared heap between processes. The only exception is binaries bigger than 64 bytes, where only a reference is copied.
When executing code in one process, only parts are updated. Let's analyze tuples, as that is the example you provided.
A tuple is actually a structure that keeps references to the actual data somewhere on the heap (except for small integers and maybe one more data type which I can't remember). When you update a tuple, using for example setelement/3, a new tuple is created with the given element replaced, however for all other elements only the reference is copied. There is one exception which I have never been able to take advantage of.
The garbage collector keeps track of each tuple and understands when it is safe to reclaim any tuple that is no longer used. It might be that the data referenced by the tuple is still in use, in which case the data itself is not collected.
As always, Erlang gives you some tools to understand exactly what is going on. The efficiency guide details how to use erts_debug:size/1 and erts_debug:flat_size/1 to understand the size of the data structure when used internally in a process and when copied. The trace tools also allows you to understand when, what and how much was garbage collected.
The record foo is of arity four (holding four words), but the whole structure is 14 words in size. Any immediate (pids, ports, small integers, atoms, catch and nil) can be stored directly in the tuples array. Any other term which can't fit into a word, such as other tuples, are not stored directly but referenced by boxed pointers (a boxed pointer is an erlang term with a forwarding address to the real eterm ... just internals).
In your case a new tuple of same arity is created and the atom foo and all the pointers are copied from the previous tuple except for index two, a, which points to the new tuple {7,8} which constitutes 3 words. In all 5 + 3 new words are created on the heap and only 3 words are copied from the old tuple the other 9 words are not touched.
Excessively large tuples are not recommended. When updating a tuple, the whole tuple, i.e the array and not the deep content, needs to copied and then updated in other to preserve a persistent data structure. This will also generate increased garbage, forcing the garbage collector to heat up which also hurts performance. The dict and array modules avoids using large tuples for this reason and have a shallow tuple tree instead.
I can definitely verify what people have already pointed out:
a record is just a tuple with the record name as the first element and all the fields just the following tuple element
when an element of a tuple is changed, updating a field in a record in your case, only the top level tuple is new, all the elements are just reused
This works just because we have immutable data. So in your example each time you update a value in a #foo record none of the data in the elements are copied and only a new 4-element tuple (5 words) is created. Erlang will never does a deep copy in this type of operation or when passing arguments in function calls.
In conclusion:
Thing = #foo{a={1,2}, b={3,4}, c={5,6}},
Thing1 = Thing#foo{a={7,8}}.
Here, if Thing is not used again, it will probably be updated in place and copying of the tuple will be avoided, as the Efficiency Guide says. (tuple and record syntax is complied into something like setelement, I think)
Thing = #ridiculously_large_record,
Thing1 = make_modified_copy(Thing),
Thing2 = make_modified_copy(Thing1),
...
Here the tuples are actually copied every time.
I guess that it would be theoretically possible make an interesting optimization to this. If the compiler could perform escape analysis on the return value of make_modified_copy and detect that the only reference to it is the one returned, in could save this information about the function. When it encounter a call the that function it would know that it is safe to modify the return value in place.
This would only be possible to do on inter module calls, because of the code replace feature.
Maybe one day we will have it.

Do objects also have some scope like methods local variables have?

i have a confusion how gabage collector decides that an object is no more in use, do object have some scope?
like if i have code
class A { in x; m1(){}}
class B {A a=new a(); a.x=10; }
so i want to know that when the object become unusable
i mean in the above code if class be reaches to end line then when it exit that class do object a can go for garbage collection, and after that A class varibale will agian hold is default value of will permanently value 10
Only declarations (type, member, local) have scope. Nothing else.
Garbage collectors work by finding and tagging all objects that are reachable from known starting points (e.g., each thread's stack, all static variables, ...), and then blowing away objects that didn't get tagged. The full explanation is usually far more complex, but this is the essence of it.
Objects do have scope as any other variable and as defined by language rules.
An object is garbage collected when there are no other objects referencing it.
GC has its more or less complex algorithm for determining that . One of them is reference counting.
When a local variabla goes out of scope it looses a reference, if refernece coutn is 0 then is garbage collected.
Garbage collection is not deterministic, that is you can't decide eactly when to garbage collect it.
Setting a variable to null will basically make the variable garbage collectable.

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