Verifying programs with heterogeneous arrays in VST - coq

I'm verifying a c program that uses arrays to store heterogeneous data - in particular, the program uses arrays to implement cons cells, where the first element of the array is an integer value, and the second element is a pointer to the next cons cell.
For example, the free operation for this list would be:
void listfree(void * x) {
if((x == 0)) {
return;
} else {
void * n = *((void **)x + 1);
listfree(n);
free(x);
return;
}
}
Note: Not shown here, but other code sections will read the values of the array and treat it as an integer.
While I understand that the natural way to express this would be as some kind of struct, the program itself is written using an array, and I can't change this.
How should I specify the structure of the memory in VST?
I've defined an lseg predicate as follows:
Fixpoint lseg (x: val) (s: (list val)) (self_card: lseg_card) : mpred := match self_card with
| lseg_card_0 => !!(x = nullval) && !!(s = []) && emp
| lseg_card_1 _alpha_513 =>
EX v : Z,
EX s1 : (list val),
EX nxt : val,
!!(~ (x = nullval)) &&
!!(s = ([(Vint (Int.repr v))] ++ s1)) &&
(data_at Tsh (tarray tint 2) [(Vint (Int.repr v)); nxt] x) *
(lseg nxt s1 _alpha_513)
end.
However, I run into troubles when trying to evaluate void *n = *(void **)x; presumably because the specification states that the memory contains an array of ints not pointers.

The issue is probably as follows, and can almost be solved as follows.
The C semantics permit casting an integer (of the right size) to a pointer, and vice versa, as long as you don't actually do any pointer operations to an integer value, or vice versa. Very likely your C program obeys those rules. But the type system of Verifiable C tries to enforce that local variables (and array elements, etc.) of integer type will never contain pointer values, and vice versa (except the special integer value 0, which is NULL).
However, Verifiable C does support a (proved-foundationally-sound) workaround to this stricter enforcement:
typedef void * int_or_ptr
#ifdef COMPCERT
__attribute((aligned(_Alignof(void*))))
#endif
;
That is: the int_or_ptr type is void*, but with the attribute "align this as void*". So it's semantically identical to void*, but the redundant attribute is a hint to the VST type system to be less restrictive about C type enforcement.
So, when I say "can almost be solved", I'm asking: Can you modify the C program to use an array of "void* aligned as void*" ?
If so, then you can proceed. Your VST verification should use int_or_ptr_type, which is a definition of type Ctypes.type provided by VST-Floyd, when referring to the C-language type of these array elements, or of local variables that these elements are loaded into.
Unfortunately, int_or_ptr_type is not documented in the reference manual (VC.pdf), which is an omission that should be correct. You can look at progs/int_or_ptr.c and progs/verif_int_or_ptr.v, but these do much more than you want or need: They axiomatize operators that distinguish odd integers from aligned pointers, which is undefined in C11 (but consistent with C11, otherwise the ocaml garbage collector could never work). That is, those axiomatized external functions are consistent with CompCert, gcc, clang; but you won't need any of them, because the only operations you're doing on int_or_pointer are the perfectly-legal "comparison with NULL" and "cast to integer" or "cast to struct foo *".

Related

How to prevent this Cyclic polynomial hash function from using a type constraint?

I am trying to implement the Cyclic polynomial hash function in f#. It uses the bit-wise operators ^^^ and <<<. Here is an example of a function that hashes an array:
let createBuzhash (pattern : array<'a>) =
let n = pattern.Length
let rec loop index pow acc =
if index < n then
loop (index+1) (pow-1) (acc ^^^ ((int pattern.[index]) <<< pow))
else
acc
loop 0 (n-1) 0
My problem is that the type of 'a will be constrained to an int, while i want this function to work with any of the types that work with bit-wise operators, for example a char. I tried using inline, but that creates some problems farther down in my library. Is there a way to fix this without using inline?
Edit for clarity: The function will be part of a library, and another hash function is provided for types that don't support the bit-wise operators. I want this function to work with arrays of numeric types and/or chars.
Edit 2 (problem solved) : The problem with inline was the way how i loaded the function from my library. instead of
let hashedPattern = library.createBuzhash targetPattern
I used this binding:
let myFunction = library.createBuzhash
let hashedPattern = myFunction targetPattern
that constraints the input type for myFunction to int, although the createBuzhash function is an inline function in the library. Changing the way I call the function fixed the type constraint problem, and inline works perfectly fine, as the answer below suggests.
In the implementation, you are converting the value in the array to an Integer using the int function as follows: int pattern.[index]
This creates a constraint on the type of array elements requiring them to be "something that can be converted to int". If you mark the function as inline, it will actually work for types like char and you'll be able to write:
createBuzhash [|'a'; 'b'|]
But there are still many other types that cannot be converted to integer using the int function.
To make this work for any type, you have to decide how you want to handle types that are not numeric. Do you want to:
Provide your own hashing function for all values?
Use the built-in .NET GetHashCode operation?
Only make your function work on numeric types and arrays of numeric types?
One option would be to add a parameter that specifies how to do the conversion:
let inline createBuzhash conv (pattern : array<'a>) =
let n = pattern.Length
let rec loop index pow acc =
if index < pattern.Length then
loop (index+1) (pow-1) (acc ^^^ ((conv pattern.[index]) <<< pow))
else
acc
loop 0 (n-1) 0
When calling createBuzhash, you now need to give it a function for hashing the elements. This works on primitive types using the int function:
createBuzhash int [| 0 .. 10 |]
createBuzhash int [|'a'; 'b'|]
But you can also use built-in F# hashing mechanism:
createBuzhash hash [| (1,"foo"); (2,"bar") |]
And you can even handle nested arrays by passing the function to itself:
createBuzhash (createBuzhash int) [| [| 1 |]; [| 2 |] |]

How does dereference work C++

I have trouble understanding what happens when calling &*pointer
int j=8;
int* p = &j;
When I print in my compiler I get the following
j = 8 , &j = 00EBFEAC p = 00EBFEAC , *p = 8 , &p = 00EBFEA0
&*p= 00EBFEAC
cout << &*p gives &*p = 00EBFEAC which is p itself
& and * have same operator precedence.I thought &*p would translate to &(*p)--> &(8) and expected compiler error.
How does compiler deduce this result?
You are stumbling over something interesting: Variables, strictly spoken, are not values, but refer to values. 8 is an integer value. After int i=8, i refers to an integer value. The difference is that it could refer to a different value.
In order to obtain the value, i must be dereferenced, i.e. the value stored in the memory location which i stands for must be obtained. This dereferencing is performed implicitly in C whenever a value of the type which the variable references is requested: i=8; printf("%d", i) results in the same output as printf("%d", 8). That is funny because variables are essentially aliases for addresses, while numeric literals are aliases for immediate values. In C these very different things are syntactically treated identically. A variable can stand in for a literal in an expression and will be automatically dereferenced. The resulting machine code makes that very clear. Consider the two functions below. Both have the same return type, int. But f has a variable in the return statement which must be dereferenced so that its value can be returned (in this case, it is returned in a register):
int i = 1;
int g(){ return 1; } // literal
int f(){ return i; } // variable
If we ignore the housekeeping code, the functions each translate into a sigle machine instruction. The corresponding assembler (from icc) is for g:
movl $1, %eax #5.17
That's pretty starightforward: Put 1 in the register eax.
By contrast, f translates to
movl i(%rip), %eax #4.17
This puts the value at the address in register rip plus offset i in the register eax. It's refreshing to see how a variable name is just an address (offset) alias to the compiler.
The necessary dereferencing should now be obvious. It would be more logical to write return *i in order to return 1, and write return i only for functions which return references — or pointers.
In your example it is indeed illogical to a degree that
int j=8;
int* p = &j;
printf("%d\n", *p);
prints 8 (i.e, p is actually dereferenced twice); but that &(*p) yields the address of the object pointed to by p (which is the address value stored in p), and is not interpreted as &(8). The reason is that in the context of the address operator a variable (or, in this case, the L-value obtained by dereferencing p) is not implicitly dereferenced the way it is in other contexts.
When the attempt was made to create a logical, orthogonal language — Algol68 —, int i=8 indeed declared an alias for 8. In order to declare a variable the long form would have been refint m = loc int := 3. Consequently what we call a pointer or reference would have had the type ref ref int because actually two dereferences are needed to obtain an integer value.
j is an int with value 8 and is stored in memory at address 00EBFEAC.
&j gives the memory address of variable j (00EBFEAC).
int* p = &j Here you define a variable p which you define being of type int *, namely a value of an address in memory where it can find an int. You assign it &j, namely an address of an int -> which makes sense.
*p gives you the value associated with the address stored in p.
The address stored in p points to an int, so *p gives you the value of that int, namely 8.
& p is the address of where the variable p itself is stored
&*p gives you the address of the value the memory address stored in p points to, which is indeed p again. &(*p) -> &(j) -> 00EBFEAC
Think about &j itself (or even &(j)). According to your logic, shouldn't j evaluate to 8 and result in &8, as well? Dereferencing a pointer or evaluating a variable results in an lvalue, which is a value that you can assign to or take the address of.
The L in "lvalue" refers to the left in "left hand side of the assignment", such as j = 10 or *p = 12. There are also rvalues, such as j + 10, or 8, which obviously cannot be assigned to.
That's just a basic explanation. In C++ there's a lot more to it, with various classes of values (but that thread might be too advanced for your current needs).

Specman: Why DAC macro interprets the type <some_name'exp> as 'string'?

I'm trying to write a DAC macro that gets as input the name of list of bits and its size, and the name of integer variable. Every element in the list should be constrained to be equal to every bit in the variable (both of the same length), i.e. (for list name list_of_bits and variable name foo and their length is 4) the macro's output should be:
keep list_of_bits[0] == foo[0:0];
keep list_of_bits[1] == foo[1:1];
keep list_of_bits[2] == foo[2:2];
keep list_of_bits[3] == foo[3:3];
My macro's code is:
define <keep_all_bits'exp> "keep_all_bits <list_size'exp> <num'name> <list_name'name>" as computed {
for i from 0 to (<list_size'exp> - 1) do {
result = appendf("%s keep %s[%d] == %s[%d:%d];",result, <list_name'name>, index, <num'name>, index, index);
};
};
The error I get:
*** Error: The type of '<list_size'exp>' is 'string', while expecting a
numeric type
...
for i from 0 to (<list_size'exp> - 1) do {
Why it interprets the <list_size'exp> as string?
Thank you for your help
All macro arguments in DAC macros are considered strings (except repetitions, which are considered lists of strings).
The point is that a macro treats its input purely syntactically, and it has no semantic information about the arguments. For example, in case of an expression (<exp>) the macro is unable to actually evaluate the expression and compute its value at compilation time, or even to figure out its type. This information is figured out at later compilation phases.
In your case, I would assume that the size is always a constant. So, first of all, you can use <num> instead of <exp> for that macro argument, and use as_a() to convert it to the actual number. The difference between <exp> and <num> is that <num> allows only constant numbers and not any expressions; but it's still treated as a string inside the macro.
Another important point: your macro itself should be a <struct_member> macro rather than an <exp> macro, because this construct itself is a struct member (namely, a constraint) and not an expression.
And one more thing: to ensure that the list size will be exactly as needed, add another constraint for the list size.
So, the improved macro can look like this:
define <keep_all_bits'struct_member> "keep_all_bits <list_size'num> <num'name> <list_name'name>" as computed {
result = appendf("keep %s.size() == %s;", <list_name'name>, <list_size'num>);
for i from 0 to (<list_size'num>.as_a(int) - 1) do {
result = appendf("%s keep %s[%d] == %s[%d:%d];",result, <list_name'name>, i, <num'name>, i, i);
};
};
Why not write is without macro?
keep for each in list_of_bits {
it == foo[index:index];
};
This should do the same, but look more readable and easier to debug; also the generation engine might take some advantage of more concise constraint.

New Scope in Coq

I'd like my own scope, to play around with long distfixes.
Declare Scope my_scope.
Delimit Scope my_scope with my.
Open Scope my_scope.
Definition f (x y a b : nat) : nat := x+y+a+b.
Notation "x < y * a = b" := (f x y a b)
(at level 100, no associativity) : my_scope.
Check (1 < 2 * 3 = 4)%my.
How do you make a new scope?
EDIT: I chose "x < y * a = b" to override Coq's operators (each with a different precedence).
The command Declare Scope does not exist. The various commands about scopes are described in section 12.2 of the Coq manual.
Your choice of an example notation has inherent problems, because it clashes with pre-defined notations, which seem to be used before your notation.
When looking at the first components the parser sees _ < _ and thinks that you are actually talking about comparison of integers, then it sees the second part as being an instance of the notation _ * _, then it sees that all that is the left hand side of an equality. And all along the parser is happy, it constructs an expression of the form:
(1 < (2 * 3)) = 4
This is constructed by the parser, and the type system has not been solicited yet. The type checker sees a natural number as the first child of (_ < _) and is happy. It sees (_ * _) as the second child and it is happy, it now knows that the first child of that product should be a nat number and it is still happy; in the end it has an equality, and the first component of this equality is in type Prop, but the second component is in type nat.
If you type Locate "_ < _ * _ = _". the answer tells you that you did define a new notation. The problem is that this notation never gets used, because the parser always finds another notation it can use before. Understanding why a notation is preferred to another one requires more knowledge of parsing technology, as alluded to in Coq's manual, chapter 12, in the sentence (obscure to me):
Coq extensible parsing is performed by Camlp5 which is essentially a LL1 parser.
You have to choose the levels of the various variables, x, y, a, and b so that none of these variables will be able to match too much of the text. For instance, I tried defining a notation close to yours, but with a starting and an ending bracket (and I guess this simplifies the task greatly).
Notation "<< x < y * a = b >>" := (f x y a b)
(x at level 59, y at level 39, a at level 59) : my_scope.
The level of x is chosen to be lower than the level of =, the level of y is chosen to be lower than the level of *, the level of a is chosen to be lower than =. The levels were obtained by reading the answer of the command Print Grammar constr. It seems to work, as the following command is accepted.
Check << 1 < 2 * 3 = 4 >>.
But you may need to include a little more engineering to have a really good notation.
To answer the actual question in your title:
The new scope gets created when you declare a notation that uses it. That is, you don’t declare a new scope my_scope separately. You just write
Notation "x <<< y" := (f x y) (at level 100, no associativity) : my_scope.
and that declares a new scope my_scope.
The answers for this question only apply to older versions of Coq. I'm not sure when it started but in at least Coq 8.13.2, Coq prefers the user to first use Declare Scope create a new scope. What the OP has in their code is Coq's preferred way to declare scopes now.
See the current manual

Performance difference between functions and pattern matching in Mathematica

So Mathematica is different from other dialects of lisp because it blurs the lines between functions and macros. In Mathematica if a user wanted to write a mathematical function they would likely use pattern matching like f[x_]:= x*x instead of f=Function[{x},x*x] though both would return the same result when called with f[x]. My understanding is that the first approach is something equivalent to a lisp macro and in my experience is favored because of the more concise syntax.
So I have two questions, is there a performance difference between executing functions versus the pattern matching/macro approach? Though part of me wouldn't be surprised if functions were actually transformed into some version of macros to allow features like Listable to be implemented.
The reason I care about this question is because of the recent set of questions (1) (2) about trying to catch Mathematica errors in large programs. If most of the computations were defined in terms of Functions, it seems to me that keeping track of the order of evaluation and where the error originated would be easier than trying to catch the error after the input has been rewritten by the successive application of macros/patterns.
The way I understand Mathematica is that it is one giant search replace engine. All functions, variables, and other assignments are essentially stored as rules and during evaluation Mathematica goes through this global rule base and applies them until the resulting expression stops changing.
It follows that the fewer times you have to go through the list of rules the faster the evaluation. Looking at what happens using Trace (using gdelfino's function g and h)
In[1]:= Trace#(#*#)&#x
Out[1]= {x x,x^2}
In[2]:= Trace#g#x
Out[2]= {g[x],x x,x^2}
In[3]:= Trace#h#x
Out[3]= {{h,Function[{x},x x]},Function[{x},x x][x],x x,x^2}
it becomes clear why anonymous functions are fastest and why using Function introduces additional overhead over a simple SetDelayed. I recommend looking at the introduction of Leonid Shifrin's excellent book, where these concepts are explained in some detail.
I have on occasion constructed a Dispatch table of all the functions I need and manually applied it to my starting expression. This provides a significant speed increase over normal evaluation as none of Mathematica's inbuilt functions need to be matched against my expression.
My understanding is that the first approach is something equivalent to a lisp macro and in my experience is favored because of the more concise syntax.
Not really. Mathematica is a term rewriter, as are Lisp macros.
So I have two questions, is there a performance difference between executing functions versus the pattern matching/macro approach?
Yes. Note that you are never really "executing functions" in Mathematica. You are just applying rewrite rules to change one expression into another.
Consider mapping the Sqrt function over a packed array of floating point numbers. The fastest solution in Mathematica is to apply the Sqrt function directly to the packed array because it happens to implement exactly what we want and is optimized for this special case:
In[1] := N#Range[100000];
In[2] := Sqrt[xs]; // AbsoluteTiming
Out[2] = {0.0060000, Null}
We might define a global rewrite rule that has terms of the form sqrt[x] rewritten to Sqrt[x] such that the square root will be calculated:
In[3] := Clear[sqrt];
sqrt[x_] := Sqrt[x];
Map[sqrt, xs]; // AbsoluteTiming
Out[3] = {0.4800007, Null}
Note that this is ~100× slower than the previous solution.
Alternatively, we might define a global rewrite rule that replaces the symbol sqrt with a lambda function that invokes Sqrt:
In[4] := Clear[sqrt];
sqrt = Function[{x}, Sqrt[x]];
Map[sqrt, xs]; // AbsoluteTiming
Out[4] = {0.0500000, Null}
Note that this is ~10× faster than the previous solution.
Why? Because the slow second solution is looking up the rewrite rule sqrt[x_] :> Sqrt[x] in the inner loop (for each element of the array) whereas the fast third solution looks up the value Function[...] of the symbol sqrt once and then applies that lambda function repeatedly. In contrast, the fastest first solution is a loop calling sqrt written in C. So searching the global rewrite rules is extremely expensive and term rewriting is expensive.
If so, why is Sqrt ever fast? You might expect a 2× slowdown instead of 10× because we've replaced one lookup for Sqrt with two lookups for sqrt and Sqrt in the inner loop but this is not so because Sqrt has the special status of being a built-in function that will be matched in the core of the Mathematica term rewriter itself rather than via the general-purpose global rewrite table.
Other people have described much smaller performance differences between similar functions. I believe the performance differences in those cases are just minor differences in the exact implementation of Mathematica's internals. The biggest issue with Mathematica is the global rewrite table. In particular, this is where Mathematica diverges from traditional term-level interpreters.
You can learn a lot about Mathematica's performance by writing mini Mathematica implementations. In this case, the above solutions might be compiled to (for example) F#. The array may be created like this:
> let xs = [|1.0..100000.0|];;
...
The built-in sqrt function can be converted into a closure and given to the map function like this:
> Array.map sqrt xs;;
Real: 00:00:00.006, CPU: 00:00:00.015, GC gen0: 0, gen1: 0, gen2: 0
...
This takes 6ms just like Sqrt[xs] in Mathematica. But that is to be expected because this code has been JIT compiled down to machine code by .NET for fast evaluation.
Looking up rewrite rules in Mathematica's global rewrite table is similar to looking up the closure in a dictionary keyed on its function name. Such a dictionary can be constructed like this in F#:
> open System.Collections.Generic;;
> let fns = Dictionary<string, (obj -> obj)>(dict["sqrt", unbox >> sqrt >> box]);;
This is similar to the DownValues data structure in Mathematica, except that we aren't searching multiple resulting rules for the first to match on the function arguments.
The program then becomes:
> Array.map (fun x -> fns.["sqrt"] (box x)) xs;;
Real: 00:00:00.044, CPU: 00:00:00.031, GC gen0: 0, gen1: 0, gen2: 0
...
Note that we get a similar 10× performance degradation due to the hash table lookup in the inner loop.
An alternative would be to store the DownValues associated with a symbol in the symbol itself in order to avoid the hash table lookup.
We can even write a complete term rewriter in just a few lines of code. Terms may be expressed as values of the following type:
> type expr =
| Float of float
| Symbol of string
| Packed of float []
| Apply of expr * expr [];;
Note that Packed implements Mathematica's packed lists, i.e. unboxed arrays.
The following init function constructs a List with n elements using the function f, returning a Packed if every return value was a Float or a more general Apply(Symbol "List", ...) otherwise:
> let init n f =
let rec packed ys i =
if i=n then Packed ys else
match f i with
| Float y ->
ys.[i] <- y
packed ys (i+1)
| y ->
Apply(Symbol "List", Array.init n (fun j ->
if j<i then Float ys.[i]
elif j=i then y
else f j))
packed (Array.zeroCreate n) 0;;
val init : int -> (int -> expr) -> expr
The following rule function uses pattern matching to identify expressions that it can understand and replaces them with other expressions:
> let rec rule = function
| Apply(Symbol "Sqrt", [|Float x|]) ->
Float(sqrt x)
| Apply(Symbol "Map", [|f; Packed xs|]) ->
init xs.Length (fun i -> rule(Apply(f, [|Float xs.[i]|])))
| f -> f;;
val rule : expr -> expr
Note that the type of this function expr -> expr is characteristic of term rewriting: rewriting replaces expressions with other expressions rather than reducing them to values.
Our program can now be defined and executed by our custom term rewriter:
> rule (Apply(Symbol "Map", [|Symbol "Sqrt"; Packed xs|]));;
Real: 00:00:00.049, CPU: 00:00:00.046, GC gen0: 24, gen1: 0, gen2: 0
We've recovered the performance of Map[Sqrt, xs] in Mathematica!
We can even recover the performance of Sqrt[xs] by adding an appropriate rule:
| Apply(Symbol "Sqrt", [|Packed xs|]) ->
Packed(Array.map sqrt xs)
I wrote an article on term rewriting in F#.
Some measurements
Based on #gdelfino answer and comments by #rcollyer I made this small program:
j = # # + # # &;
g[x_] := x x + x x ;
h = Function[{x}, x x + x x ];
anon = Table[Timing[Do[ # # + # # &[i], {i, k}]][[1]], {k, 10^5, 10^6, 10^5}];
jj = Table[Timing[Do[ j[i], {i, k}]][[1]], {k, 10^5, 10^6, 10^5}];
gg = Table[Timing[Do[ g[i], {i, k}]][[1]], {k, 10^5, 10^6, 10^5}];
hh = Table[Timing[Do[ h[i], {i, k}]][[1]], {k, 10^5, 10^6, 10^5}];
ListLinePlot[ {anon, jj, gg, hh},
PlotStyle -> {Black, Red, Green, Blue},
PlotRange -> All]
The results are, at least for me, very surprising:
Any explanations? Please feel free to edit this answer (comments are a mess for long text)
Edit
Tested with the identity function f[x] = x to isolate the parsing from the actual evaluation. Results (same colors):
Note: results are very similar to this Plot for constant functions (f[x]:=1);
Pattern matching seems faster:
In[1]:= g[x_] := x*x
In[2]:= h = Function[{x}, x*x];
In[3]:= Do[h[RandomInteger[100]], {1000000}] // Timing
Out[3]= {1.53927, Null}
In[4]:= Do[g[RandomInteger[100]], {1000000}] // Timing
Out[4]= {1.15919, Null}
Pattern matching is also more flexible as it allows you to overload a definition:
In[5]:= g[x_] := x * x
In[6]:= g[x_,y_] := x * y
For simple functions you can compile to get the best performance:
In[7]:= k[x_] = Compile[{x}, x*x]
In[8]:= Do[k[RandomInteger[100]], {100000}] // Timing
Out[8]= {0.083517, Null}
You can use function recordSteps in previous answer to see what Mathematica actually does with Functions. It treats it just like any other Head. IE, suppose you have the following
f = Function[{x}, x + 2];
f[2]
It first transforms f[2] into
Function[{x}, x + 2][2]
At the next step, x+2 is transformed into 2+2. Essentially, "Function" evaluation behaves like an application of pattern matching rules, so it shouldn't be surprising that it's not faster.
You can think of everything in Mathematica as an expression, where evaluation is the process of rewriting parts of the expression in a predefined sequence, this applies to Function like to any other head