I am using Win32::API to call an arbitary function exported in a DLL which accepts a C++ structure pointer.
struct PluginInfo {
int nStructSize;
int nType;
int nVersion;
int nIDCode;
char szName[ 64 ];
char szVendor[ 64 ];
int nCertificate;
int nMinAmiVersion;
};
As we need to use the "pack" function to construct the structure and need to pass an argument
my $name = " " x 64;
my $vendor = " " x 64;
my $pluginInfo = pack('IIIIC64C64II',0,0,0,0,$name,$vendor,0,0);
Its not constructing the structure properly.
It seems that length argument applied to C will gobble those many arguments.
Can some one please suggest the best way to construct this structure form Perl and passon to dll call.
Thanks in advance,
Naga Kiran
Use Z (NUL-padded string) in your template, as in
my $pluginInfo = pack('IIIIZ64Z64II',0,0,0,0,$name,$vendor,0,0);
Also, take a look at Win32::API::Struct, which is part of the Win32::API module.
For anything complicated, check out Convert::Binary::C. It may seem daunting at first, but once you realize its power, it's an eye opener.
Update: Let me add a bit of information. You need to have a look at a specific section of the module's manpage for the prime reason to use it. I'll quote it for convenience:
Why use Convert::Binary::C?
Say you want to pack (or unpack) data
according to the following C
structure:
struct foo {
char ary[3];
unsigned short baz;
int bar;
};
You could of course use Perl's pack
and unpack functions:
#ary = (1, 2, 3);
$baz = 40000;
$bar = -4711;
$binary = pack 'c3 Si', #ary, $baz, $bar;
But this implies that the struct
members are byte aligned. If they were
long aligned (which is the default for
most compilers), you'd have to write
$binary = pack 'c3 x S x2 i', #ary, $baz, $bar;
which doesn't really increase
readability.
Now imagine that you need to pack the
data for a completely different
architecture with different byte
order. You would look into the pack
manpage again and perhaps come up with
this:
$binary = pack 'c3 x n x2 N', #ary, $baz, $bar;
However, if you try to unpack $foo
again, your signed values have turned
into unsigned ones.
All this can still be managed with
Perl. But imagine your structures get
more complex? Imagine you need to
support different platforms? Imagine
you need to make changes to the
structures? You'll not only have to
change the C source but also dozens of
pack strings in your Perl code. This
is no fun. And Perl should be fun.
Now, wouldn't it be great if you could
just read in the C source you've
already written and use all the types
defined there for packing and
unpacking? That's what
Convert::Binary::C does.
Related
I have a boost::multiprecision::cpp_int in big endian and have to change it to little endian. How can I do that? I tried with boost::endian::conversion but that did not work.
boost::multiprecision::cpp_int bigEndianInt("0xe35fa931a0000*);
boost::multiprecision::cpp_int littleEndianInt;
littleEndianIn = boost::endian::endian_reverse(m_cppInt);
The memory layout of boost multi-precision types is implementation detail. So you cannot assume much about it anyways (they're not supposed to be bitwise serializable).
Just read a random section of the docs:
MinBits
Determines the number of Bits to store directly within the object before resorting to dynamic memory allocation. When zero, this field is determined automatically based on how many bits can be stored in union with the dynamic storage header: setting a larger value may improve performance as larger integer values will be stored internally before memory allocation is required.
It's not immediately clear that you have any chance at some level of "normal int behaviour" in memory layout. The only exception would be when MinBits==MaxBits.
Indeed, we can static_assert that the size of cpp_int with such backend configs match the corresponding byte-sizes.
It turns out that there's even a promising tag in the backend base-class to indicate "triviality" (this is truly promising): trivial_tag, so let's use it:
Live On Coliru
#include <boost/multiprecision/cpp_int.hpp>
namespace mp = boost::multiprecision;
template <int bits> using simple_be =
mp::cpp_int_backend<bits, bits, mp::unsigned_magnitude>;
template <int bits> using my_int =
mp::number<simple_be<bits>, mp::et_off>;
using my_int8_t = my_int<8>;
using my_int16_t = my_int<16>;
using my_int32_t = my_int<32>;
using my_int64_t = my_int<64>;
using my_int128_t = my_int<128>;
using my_int192_t = my_int<192>;
using my_int256_t = my_int<256>;
template <typename Num>
constexpr bool is_trivial_v = Num::backend_type::trivial_tag::value;
int main() {
static_assert(sizeof(my_int8_t) == 1);
static_assert(sizeof(my_int16_t) == 2);
static_assert(sizeof(my_int32_t) == 4);
static_assert(sizeof(my_int64_t) == 8);
static_assert(sizeof(my_int128_t) == 16);
static_assert(is_trivial_v<my_int8_t>);
static_assert(is_trivial_v<my_int16_t>);
static_assert(is_trivial_v<my_int32_t>);
static_assert(is_trivial_v<my_int64_t>);
static_assert(is_trivial_v<my_int128_t>);
// however it doesn't scale
static_assert(sizeof(my_int192_t) != 24);
static_assert(sizeof(my_int256_t) != 32);
static_assert(not is_trivial_v<my_int192_t>);
static_assert(not is_trivial_v<my_int256_t>);
}
Conluding: you can have trivial int representation up to a certain point, after which you get the allocator-based dynamic-limb implementation no matter what.
Note that using unsigned_packed instead of unsigned_magnitude representation never leads to a trivial backend implementation.
Note that triviality might depend on compiler/platform choices (it's likely that cpp_128_t uses some builtin compiler/standard library support on GCC, e.g.)
Given this, you MIGHT be able to pull of what you wanted to do with hacks IF your backend configuration support triviality. Sadly I think it requires you to manually overload endian_reverse for 128 bits case, because the GCC builtins do not have __builtin_bswap128, nor does Boost Endian define things.
I'd suggest working off the information here How to make GCC generate bswap instruction for big endian store without builtins?
Final Demo (not complete)
#include <boost/multiprecision/cpp_int.hpp>
#include <boost/endian/buffers.hpp>
namespace mp = boost::multiprecision;
namespace be = boost::endian;
template <int bits> void check() {
using T = mp::number<mp::cpp_int_backend<bits, bits, mp::unsigned_magnitude>, mp::et_off>;
static_assert(sizeof(T) == bits/8);
static_assert(T::backend_type::trivial_tag::value);
be::endian_buffer<be::order::big, T, bits, be::align::no> buf;
buf = T("0x0102030405060708090a0b0c0d0e0f00");
std::cout << std::hex << buf.value() << "\n";
}
int main() {
check<128>();
}
(Changing be::order::big to be::order::native obviously makes it compile. The other way to complete it would be to have an ADL accessible overload for endian_reverse for your int type.)
This is both trivial and in the general case unanswerable, let me explain:
For a general N-bit integer, where N is a large number, there is unlikely to be any well defined byte order, indeed even for 64 and 128 bit integers there are more than 2 possible orders in use: https://en.wikipedia.org/wiki/Endianness#Middle-endian.
On any platform, with any native endianness you can always extract the bytes of a cpp_int, the first example here: https://www.boost.org/doc/libs/1_73_0/libs/multiprecision/doc/html/boost_multiprecision/tut/import_export.html#boost_multiprecision.tut.import_export.examples shows you how. When exporting bytes like this, they are always most significant byte first, so you can subsequently rearrange them how you wish. You should not however, rearrange them and load them back into a cpp_int as the class won't know what to do with the result!
If you know that the value is small enough to fit into a native integer type, then you can simply cast to the native integer and use a system API on the result. As in endian_reverse(static_cast<int64_t>(my_cpp_int)). Again, don't assign the result back into a cpp_int as it requires native byte order.
If you wish to check whether a value is small enough to fit in an N-bit integer for the approach above, you can use the msb function, which returns the index of the most significant bit in the cpp_int, add one to that to obtain the number of bits used, and filter out the zero case and the code looks like:
unsigned bits_used = my_cpp_int.is_zero() ? 0 : msb(my_cpp_int) + 1;
Note that all of the above use completely portable code - no hacking of the underlying implementation is required.
Consider the below function,
public static int foo(int x){
return x + 5;
}
Now, let us call it,
int in = /*Input taken from the user*/;
int x = foo(10); // ... (1)
int y = foo(in); // ... (2)
Here, can the compiler change
int x = foo(10); // ... (1)
to
int x = 15; // ... (1)
by evaluating the function call during compile time since the input to the function is available during compile time ?
I understand this is not possible during the call marked (2) because the input is available only during run time.
I do not want to know a way of doing it in any specific language. I would like to know why this can or can not be a feature of a compiler itself.
C++ does have a method for this:
Have a read up on the 'constexpr' keyword in C++11, it allows compile time evaluation of functions.
They have a limitation: the function must be a return statement (not multiple lines of code), but can call other constexpr functions (C++14 does not have this limitation AFAIK).
static constexpr int foo(int x){
return x + 5;
}
EDIT:
Why a compiler might not evaluate a function (just my guess):
It might not be appropriate to remove a function by evaluating it without being told.
The function could be used in different compilation units, and with static/dynamic inputs: thus evaluating it in some circumstances and adding a call in other places.
This use would provide inconsistent execution times (especially on a deterministic platform like AVR) where timing may be important, or at least need to be predictable.
Also interrupts (and how the compiler interacts with them) may come into play here.
EDIT:
constexpr is actually stronger -- it requires that the compiler do this. The compiler is free to fold away functions without constexpr, but the programmer can't rely on it doing so.
Can you give an example in the case where the user would have benefited from this but the compiler chose not to do it ?
inline functions may, or may not resolve to constant expressions which could be optimized into the end result.
However, a constexpr guarantees it. An inline function cannot be used as a compile time constant whereas constexpr can allow you to formulate compile time functions and more so, objects.
A basic example where constexpr makes a guarantee that inline cannot.
constexpr int foo( int a, int b, int c ){
return a+b+c;
}
int array[ foo(1, 2, 3) ];
And the same as a simple object.
struct Foo{
constexpr Foo( int a, int b, int c ) : val(a+b+c){}
int val;
};
constexpr Foo foo( 1,2,4 );
int array[ foo.val ];
Unless foo.val is a compile time constant, the code above will not compile.
Even as just a function, an inline function has no guarantee. And the linker can also do inlining over multiple compilation units, after the syntax has been compiled (array bounds checked for integer constants).
This is kind of like meta-programming, but without the templates. Of course these examples do not do the topic justice, however very complex solutions would benefit from the ability to use objects and functional programming to achieve a result.
Yes, evaluation can happen during compile time. This comes under the heading of constant folding and function inlining, both of which are common optimizations for optimizing compilers.
Many languages do not have strong distinction between "compile time" and "run time", but the general rule is that the language defines an "execution model" which defines the behavior of any particular program with any particular input (or specifies that it is undefined). The compiler must produce an executable that can read any input and produce the corresponding output as defined by the execution model. What happens inside the executable doesn't matter -- as long as the externally viewed behavior is correct.
Here "input", "output" and "behavior" includes all possible interactions with the environment that are defined in the execution model, including timing effects.
I am looking for a general-purpose way of defining textual expressions which allow a value to be validated.
For example, I have a value which should only be set to 1, 2, 3, 10, 11, or 12.
Its constraint might be defined as: (value >= 1 && value <= 3) || (value >= 10 && value <= 12)
Or another value which can be 1, 3, 5, 7, 9 etc... would have a constraint like value % 2 == 1 or IsOdd(value).
(To help the user correct invalid values, I'd like to show the constraint - so something descriptive like IsOdd is preferable.)
These constraints would be evaluated both on client-side (after user input) and server-side.
Therefore a multi-platform solution would be ideal (specifically Win C#/Linux C++).
Is there an existing language/project which allows evaluation or parsing of similar simple expressions?
If not, where might I start creating my own?
I realise this question is somewhat vague as I am not entirely sure what I am after. Searching turned up no results, so even some terms as a starting point would be helpful. I can then update/tag the question accordingly.
You may want to investigate dependently typed languages like Idris or Agda.
The type system of such languages allows encoding of value constraints in types. Programs that cannot guarantee the constraints will simply not compile. The usual example is that of matrix multiplication, where the dimensions must match. But this is so to speak the "hello world" of dependently typed languages, the type system can do much more for you.
If you end up starting your own language I'd try to stay implementation-independent as long as possible. Look for the formal expression grammars of a suitable programming language (e.g. C) and add special keywords/functions as required. Once you have a formal definition of your language, implement a parser using your favourite parser generator.
That way, even if your parser is not portable to a certain platform you at least have a formal standard from where to start a separate parser implementation.
You may also want to look at creating a Domain Specific Language (DSL) in Ruby. (Here's a good article on what that means and what it would look like: http://jroller.com/rolsen/entry/building_a_dsl_in_ruby)
This would definitely give you the portability you're looking for, including maybe using IronRuby in your C# environment, and you'd be able to leverage the existing logic and mathematical operations of Ruby. You could then have constraint definition files that looked like this:
constrain 'wakeup_time' do
6 <= value && value <= 10
end
constrain 'something_else' do
check (value % 2 == 1), MustBeOdd
end
# constrain is a method that takes one argument and a code block
# check is a function you've defined that takes a two arguments
# MustBeOdd is the name of an exception type you've created in your standard set
But really, the great thing about a DSL is that you have a lot of control over what the constraint files look like.
there are a number of ways to verify a list of values across multiple languages. My preferred method is to make a list of the permitted values and load them into a dictionary/hashmap/list/vector (dependant on the language and your preference) and write a simple isIn() or isValid() function, that will check that the value supplied is valid based on its presence in the data structure. The beauty of this is that the code is trivial and can be implemented in just about any language very easily. for odd-only or even-only numeric validity again, a small library of different language isOdd() functions will suffice: if it isn't odd it must by definition be even (apart from 0 but then a simple exception can be set up to handle that, or you can simply specify in your code documentation that for logical purposes your code evaluates 0 as odd/even (your choice)).
I normally cart around a set of c++ and c# functions to evaluate isOdd() for similar reasons to what you have alluded to, and the code is as follows:
C++
bool isOdd( int integer ){ return (integer%2==0)?false:true; }
you can also add inline and/or fastcall to the function depending on need or preference; I tend to use it as an inline and fastcall unless there is a need to do otherwise (huge performance boost on xeon processors).
C#
Beautifully the same line works in C# just add static to the front if it is not going to be part of another class:
static bool isOdd( int integer ){ return (integer%2==0)?false:true; }
Hope this helps, in any event let me know if you need any further info:)
Not sure if it's what you looking for, but judging from your starting conditions (Win C#/Linux C++) you may not need it to be totally language agnostic. You can implement such a parser yourself in C++ with all the desired features and then just use it in both C++ and C# projects - thus also bypassing the need to add external libraries.
On application design level, it would be (relatively) simple - you create a library which is buildable cross-platform and use it in both projects. The interface may be something simple like:
bool VerifyConstraint_int(int value, const char* constraint);
bool VerifyConstraint_double(double value, const char* constraint);
// etc
Such interface will be usable both in Linux C++ (by static or dynamic linking) and in Windows C# (using P/Invoke). You can have same codebase compiling on both platforms.
The parser (again, judging from what you've described in the question) may be pretty simple - a tree holding elements of types Variable and Expression which can be Evaluated with a given Variable value.
Example class definitions:
class Entity {public: virtual VARIANT Evaluate() = 0;} // boost::variant may be used typedef'd as VARIANT
class BinaryOperation: public Entity {
private:
Entity& left;
Entity& right;
enum Operation {PLUS,MINUS,EQUALS,AND,OR,GREATER_OR_EQUALS,LESS_OR_EQUALS};
public:
virtual VARIANT Evaluate() override; // Evaluates left and right operands and combines them
}
class Variable: public Entity {
private:
VARIANT value;
public:
virtual VARIANT Evaluate() override {return value;};
}
Or, you can just write validation code in C++ and use it both in C# and C++ applications :)
My personal choice would be Lua. The downside to any DSL is the learning curve of a new language and how to glue the code with the scripts but I've found Lua has lots of support from the user base and several good books to help you learn.
If you are after making somewhat generic code that a non programmer can inject rules for allowable input it's going to take some upfront work regardless of the route you take. I highly suggest not rolling your own because you'll likely find people wanting more features that an already made DSL will have.
If you are using Java then you can use the Object Graph Navigation Library.
It enables you to write java applications that can parse,compile and evaluate OGNL expressions.
OGNL expressions include basic java,C,C++,C# expressions.
You can compile an expression that uses some variables, and then evaluate that expression
for some given variables.
An easy way to achieve validation of expressions is to use Python's eval method. It can be used to evaluate expressions just like the one you wrote. Python's syntax is easy enough to learn for simple expressions and english-like. Your expression example is translated to:
(value >= 1 and value <= 3) or (value >= 10 and value <= 12)
Code evaluation provided by users might pose a security risk though as certain functions could be used to be executed on the host machine (such as the open function, to open a file). But the eval function takes extra arguments to restrict the allowed functions. Hence you can create a safe evaluation environment.
# Import math functions, and we'll use a few of them to create
# a list of safe functions from the math module to be used by eval.
from math import *
# A user-defined method won't be reachable in the evaluation, as long
# as we provide the list of allowed functions and vars to eval.
def dangerous_function(filename):
print open(filename).read()
# We're building the list of safe functions to use by eval:
safe_list = ['math','acos', 'asin', 'atan', 'atan2', 'ceil', 'cos', 'cosh', 'degrees', 'e', 'exp', 'fabs', 'floor', 'fmod', 'frexp', 'hypot', 'ldexp', 'log', 'log10', 'modf', 'pi', 'pow', 'radians', 'sin', 'sinh', 'sqrt', 'tan', 'tanh']
safe_dict = dict([ (k, locals().get(k, None)) for k in safe_list ])
# Let's test the eval method with your example:
exp = "(value >= 1 and value <= 3) or (value >= 10 and value <= 12)"
safe_dict['value'] = 2
print "expression evaluation: ", eval(exp, {"__builtins__":None},safe_dict)
-> expression evaluation: True
# Test with a forbidden method, such as 'abs'
exp = raw_input("type an expression: ")
-> type an expression: (abs(-2) >= 1 and abs(-2) <= 3) or (abs(-2) >= 10 and abs(-2) <= 12)
print "expression evaluation: ", eval(exp, {"__builtins__":None},safe_dict)
-> expression evaluation:
-> Traceback (most recent call last):
-> File "<stdin>", line 1, in <module>
-> File "<string>", line 1, in <module>
-> NameError: name 'abs' is not defined
# Let's test it again, without any extra parameters to the eval method
# that would prevent its execution
print "expression evaluation: ", eval(exp)
-> expression evaluation: True
# Works fine without the safe dict! So the restrictions were active
# in the previous example..
# is odd?
def isodd(x): return bool(x & 1)
safe_dict['isodd'] = isodd
print "expression evaluation: ", eval("isodd(7)", {"__builtins__":None},safe_dict)
-> expression evaluation: True
print "expression evaluation: ", eval("isodd(42)", {"__builtins__":None},safe_dict)
-> expression evaluation: False
# A bit more complex this time, let's ask the user a function:
user_func = raw_input("type a function: y = ")
-> type a function: y = exp(x)
# Let's test it:
for x in range(1,10):
# add x in the safe dict
safe_dict['x']=x
print "x = ", x , ", y = ", eval(user_func,{"__builtins__":None},safe_dict)
-> x = 1 , y = 2.71828182846
-> x = 2 , y = 7.38905609893
-> x = 3 , y = 20.0855369232
-> x = 4 , y = 54.5981500331
-> x = 5 , y = 148.413159103
-> x = 6 , y = 403.428793493
-> x = 7 , y = 1096.63315843
-> x = 8 , y = 2980.95798704
-> x = 9 , y = 8103.08392758
So you can control the allowed functions that should be used by the eval method, and have a sandbox environment that can evaluate expressions.
This is what we used in a previous project I worked in. We used Python expressions in custom Eclipse IDE plug-ins, using Jython to run in the JVM. You could do the same with IronPython to run in the CLR.
The examples I used in part inspired / copied from the Lybniz project explanation on how to run a safe Python eval environment. Read it for more details!
You might want to look at Regular-Expressions or RegEx. It's proven and been around for a long time. There's a regex library all the major programming/script languages out there.
Libraries:
C++: what regex library should I use?
C# Regex Class
Usage
Regex Email validation
Regex to validate date format dd/mm/yyyy
[It seems my explanations and expectations are not clear at all, so I added precision on how I'd like to use the feature at the end of the post]
I'm currently working on grammars using boost qi. I had a loop construction for a rule cause I needed to build it from the elements of a vector. I have re-written it with simple types, and it looks like:
#include <string>
// using boost 1.43.0
#include <boost/spirit/include/qi.hpp>
#include <boost/spirit/include/qi_eps.hpp>
#include <boost/spirit/include/phoenix.hpp>
namespace bqi = boost::spirit::qi;
typedef const char* Iterator;
// function that you can find [here][1]
template<typename P> void test_phrase_parser(char const* input, P const& p, bool full_match = true);
int main()
{
// my working rule type:
bqi::rule<Iterator, std::string()> myLoopBuiltRule;
std::vector<std::string> v;
std::vector<std::string>::const_iterator iv;
v.push_back("abc");
v.push_back("def");
v.push_back("ghi");
v.push_back("jkl");
myLoopBuiltRule = (! bqi::eps);
for(iv = v.begin() ; iv != v.end() ; iv++)
{
myLoopBuiltRule =
myLoopBuiltRule.copy() [ bqi::_val = bqi::_1 ]
| bqi::string(*iv) [ bqi::_val = bqi::_1 ]
;
}
debug(myLoopBuiltRule);
char s[] = " abc ";
test_phrase_parser(s, myLoopBuiltRule);
}
(Looks like here does not want to be replaced by corresponding hyperlink, so here is the address to find function test_phrase_parser(): http://www.boost.org/doc/libs/1_43_0/libs/spirit/doc/html/spirit/qi/reference/basics.html)
All was for the best in the best of all worlds... until I had to pass an argument to this rule. Here is the new rule type:
// my not-anymore-working rule type:
bqi::rule<Iterator, std::string(int*)> myLoopBuiltRule;
'int*' type is for example purpose only, my real pointer is adressing a much more complex class... but still a mere pointer.
I changed my 'for' loop accordingly, i.e.:
for(iv = v.begin() ; iv != v.end() ; iv++)
{
myLoopBuiltRule =
myLoopBuiltRule.copy()(bqi::_r1) [ bqi::_val = bqi::_1 ]
| bqi::string(*iv) [ bqi::_val = bqi::_1 ]
;
}
I had to add a new rule because test_phrase_parser() cannot guess which value is to be given to the int pointer:
bqi::rule<Iterator> myInitialRule;
And change everything that followed the for loop:
myInitialRule = myLoopBuiltRule((int*)NULL);
debug(myLoopBuiltRule);
char s[] = " abc ";
test_phrase_parser(s, myInitialRule);
Then everything crashed:
/home/sylvain.darras/software/repository/software/external/include/boost/boost_1_43_0/boost/spirit/home/qi/nonterminal/rule.hpp:199: error: no matching function for call to ‘assertion_failed(mpl_::failed************ (boost::spirit::qi::rule<Iterator, T1, T2, T3, T4>::operator=(const Expr&)
Then I got crazy and tried:
myLoopBuiltRule =
myLoopBuiltRule.copy(bqi::_r1) [ bqi::_val = bqi::_1 ]
| bqi::string(*iv) [ bqi::_val = bqi::_1 ]
-->
error: no matching function for call to ‘boost::spirit::qi::rule<const char*, std::string(int*), boost::fusion::unused_type, boost::fusion::unused_type, boost::fusion::unused_type>::copy(const boost::phoenix::actor<boost::spirit::attribute<1> >&)’
Then I got mad and wrote:
myLoopBuiltRule =
myLoopBuiltRule(bqi::_r1) [ bqi::_val = bqi::_1 ]
| bqi::string(*iv) [ bqi::_val = bqi::_1 ]
Which compiles since it is perfectly syntactically correct, but which magnificently stack overflows coz it happily, nicely, recursively, calls itself to death...
Then I lost my mind and typed:
myLoopBuiltRule =
jf jhsgf jshdg fjsdgh fjsg jhsdg jhg sjfg jsgh df
Which, as you probably expect, has failed to compile.
You imagine that before writing the above novel, I checked out on the web, but didn't find out anything related to copy() and argument passing in the same time. Has anyone already experienced this problem ? Have I missed something ?
Be assured that any help will be really really appreciated.
PS: Great thanks to hkaiser who has, without knowing it, answered a lot of my boost::qi problems through google (but this one).
Further information:
The purpose of my parser is to read files written in a given language L. The purpose of my post is to propagate my "context" (i.e.: variable definitions and especially constant values, so I can compute expressions).
The number of variable types I handle is small, but it's bound to grow, so I keep these types in a container class. I can loop on these managed types.
So, let's consider a pseudo-algorithm of what I would like to achive:
LTypeList myTypes;
LTypeList::const_iterator iTypes;
bqi::rule<Iterator, LType(LContext*)> myLoopBuiltRule;
myLoopBuiltRule = (! bqi::eps);
for(iTypes = myTypes.begin() ; iTypes != myTypes.end() ; iTypes++)
{
myLoopBuiltRule =
myLoopBuiltRule.copy()(bqi::_r1) [ bqi::_val = bqi::_1 ]
| iTypes->getRule()(bqi::_r1) [ bqi::_val = bqi::_1 ]
}
This is done during initialization and then myLoopBuiltRule is used and reused with different LContext*, parsing multiple types. And since some L types can have bounds, which are integer expressions, and that these integer expressions can exhibit constants, I (think that I) need my inherited attribute to take my LContext around and be able to compute expression value.
Hope I've been clearer in my intentions.
Note I just extended my answer with a few more informational links. In this particular case I have a hunch that you could just get away with the Nabialek trick and replacing the inherited attribute with a corresponding qi::locals<> instead. If I have enough time, I might work out a demonstration later.
Caveats, expositioning the problem
Please be advised that there are issues when copying proto expression trees and spirit parser expressions in particular - it will create dangling references as the internals are not supposed to live past the end of the containing full expressions. See BOOST_SPIRIT_AUTO on Zero to 60 MPH in 2 seconds!
Also see these answers which also concerns themselves with building/composing rules on the fly (at runtime):
Generating Spirit parser expressions from a variadic list of alternative parser expressions
Can Boost Spirit Rules be parameterized which demonstrates how to return rules from a function using boost::proto::deepcopy (like BOOST_SPIRIT_AUTO does, actually)
Nabialek Trick
In general, I'd very strongly advise against combining rules at runtime. Instead, if you're looking to 'add alternatives' to a rule at runtime, you can always use qi::symbols<> instead. The trick is to store a rule in the symbol-table and use qi::lazy to call the rule. In particular, this is known as the Nabialek Trick.
I have a toy command-line arguments parser here that demonstrates how you could use this idiom to match a runtime-defined set of command line arguments:
https://gist.github.com/sehe/2a556a8231606406fe36
Limitations of qi::lazy, what's next?
Unfortunately, qi::lazy does not support inherited arguments see e.g.
http://boost.2283326.n4.nabble.com/pass-inhertited-attributes-to-nabialek-trick-td2679066.html
You might be better off writing a custom parser component, as documented here:
http://boost-spirit.com/home/articles/qi-example/creating-your-own-parser-component-for-spirit-qi/
I'll try to find some time to work out a sample that replaces inherited arguments by qi::locals later.
I'm experimenting with the frama-c value analyzer to evaluate C-Code, which is actually threaded.
I want to ignore any threading problems that might occur und just inspect the possible values for a single thread. So far this works by setting the entry point to where the thread starts.
Now to my problem: Inside one thread I read values that are written by another thread, because frama-c does not (and should not?) consider threading (currently) it assumes my variable is in some broad range, but I know that the range is in fact much smaller.
Is it possible to tell the value analyzer the value range of this variable?
Example:
volatile int x = 0;
void f() {
while(x==0)
sleep(100);
...
}
Here frama-c detects that x is volatile and thus has range [--..--], but I know what the other thread will write into x, and I want to tell the analyzer that x can only be 0 or 1.
Is this possible with frama-c, especially in the gui?
Thanks in advance
Christian
This is currently not possible automatically. The value analysis considers that volatile variables always contain the full range of values included in their underlying type. There however exists a proprietary plug-in that transforms accesses to volatile variables into calls to user-supplied function. In your case, your code would be transformed into essentially this:
int x = 0;
void f() {
while(1) {
x = f_volatile_x();
if (x == 0)
sleep(100);
...
}
By specifying f_volatile_x correctly, you can ensure it returns values between 0 and 1 only.
If the variable 'x' is not modified in the thread you are studying, you could also initialize it at the beginning of the 'main' function with :
x = Frama_C_interval (0, 1);
This is a function defined by Frama-C in ...../share/frama-c/builtin.c so you have to add this file to your inputs when you use it.