Free java brainfuck compiler 2.0 software for linux

The Java Brainfuck Compiler is a compiler for the uniquely powerful Brainfuck language, which produces Java bytecode that will run on any Java Virtual Machine (with no intermediate steps such as going by way of Java code).

Intel C++ Compiler application is a full fledged C/C++ compiler and debugger suite. Its aim is to provide outstanding performance for all Intel 32-bit and 64-bit processors, while not requiring the need for porting applications from other compilers.

It provides optimization technology, threaded application support, and features to take advantage of Hyper-Threading technology. It is substantially source and object code compatible with GNU C, providing fullest compatibility with GCC and G++ 3.x/4.x both in terms of code and of API. It is thereby also easy to integrate with existing development environments.

JavaNativeCompiler (JNC) is a Java to native compiler. The project allows AOT (ahead of time) compilation of your Java applications. With JNC, you can create real standalone native binaries (.exe on Windows) which will no longer depend on a JRE.
This is especially useful when applications have to be deployed to end-users. All vexatious problems of deploying Java applications can be solved by compiling them to native. They will be:
- Easy to deploy
No JRE dependency. Most end-users dont know what they have installed.
No more problems on how to create an executable file out of a JAR or class file.
- Hard to decompile
Java can easily be decompiled. Native compilation will protect your source code.
- Run fast from the start
No more overhead for loading a JRE.
Enhancements:
- This release fixes a couple of problems with AWT/Swing and XML.
- It also once again contains a version for Linux.
- The compiler binary downloads are smaller.

GMP compiler tool simplifies the use of GMP, the GNU multiple precision library. It scans a C source file for specially marked GMPS arithmetic expressions and replaces them with plain C.
The abbreviation gmpc stands for GMP compiler, or alternatively GMPS-to-C compiler. GMPS arithmetic expressions are straightforward infix expressions which transparently support the special types mpq_t, mpz_t and mpf_t as defined by GMP. GMPS means, rather unimaginatively, `GMP script.
No dependencies are added to the resulting C source, so there is no need to include additional header files or link with special libraries other than GMP.
Invoking gmpc
To translate a .gmpc file to C source, at least the input and output files must be given. The most concise invocation would look like this:
gmpc -o foo.c foo.gmpc
This will translate foo.gmpc into foo.c.
It is highly recommended to enable all warnings with the -Wall switch:
gmpc -Wall -o foo.gmpc foo.c
Other switches can be used to change the default behaviour of gmpc. They are listed in the following sections.
Enhancements:
- Added support for C-like compound assignments, increment and decrement operators.
- Fixed an assignment precedence bug.
- Temporary variables and constants are grouped together to make generated code more readable.
- Added Doxygen comments and configuration file.

Portable Object Compiler project consists of a set of Objective-C class libraries and a precompiler (translator) that generates plain C code.
Main features:
- Easy to install or to modify.
- Works on many systems with the native cc, debugger, profiler etc. (Unix, Windows, Macintosh, Beos, OpenVMS etc. see Platforms.txt file)
- Option for reference counted memory management (-refcnt). This uses the native malloc(), free() etc. but the compiler generates statements for keeping track of references (Tested on a few platforms, such as IRIX 5.2 with the SGI malloc).
- Built-in possibility of tracing Objective C messages. (OBJCRTMSG)
- Straightforward "C" messenger; "inline cache" messenger. Forwarding C messenger (to support -doesNotUnderstand:).
- All classes get a +initialize message at start-up, rather than each class receives a +initialize before it receives its first message.
- Some support for translating Objective-C to Smalltalk (-st80 option)
- Automatic archiver. Compiler generates code for classes to save and load objects to and from disk (for all instance variables of type "id").
- Option for Garbage Collection (using Boehm gc package). Tested on some UNIXes and WIN32. Option for reference counted memory management (doesnt require Boehm).
- Exception handling scheme (using Objective-C Blocks) that allows to specify a default handler to be executed.
- Supports dynamically loading Objective-C modules on Windows, FreeBSD, HP-UX, Linux, IRIX, Digital Unix etc.
- Has a switch for double indirection for Object identifiers (id as a handle instead of a pointer). (-become: method)
- Supports forwarding messages (-doesNotUnderstand: method)
- Support for Embedded SQL in Objective-C (Informix only for now)
- Great system for experimentation with your own additions/extensions to Objective C !

cid-compiler is a language tool to easily create C code with object oriented features. Its compiler generates header (.h) files and implementations (.c) from a specification file (.i).

The generated C code consists of a struct, a opaque pointer to it (in the header file) and rewritten functions. The defined functions will get prefixed with the class name, they will also get a new first argument that is a pointer to the newly defined struct.

Functions that do not have a return value are considered constructors and will not get a new 1st argument but will automatically get a return value of pointer to the struct. The place between @class "name" and @attributes is e. g. for include statements and will make it into the header file.

To ease renaming the class, you can use the define CLASS, which will always be a define to a pointer of the new struct type.

Interface example

@class cstring
#include < stdio.h >
#include < string.h >
@attributes
char *c;
@methods
new(char *n) {
CLASS i = NEWCLASS;
i->c = strdup(n);
return i;
}
int length() {
return strlen(this->c);
}
@end

will yield a cstring.h file:
#ifndef _CSTRING_H_
#define _CSTRING_H_
#include < stdio.h >
#include < string.h >
typedef struct cstring *cstring;
cstring cstring_new(char *n);
int cstring_length(cstring this);
#endif

and a cstring.c file:
#include "cstring.h"
#define CLASS cstring
#define NEWCLASS malloc(sizeof(struct cstring));
#define NEWCLASS_M malloc(sizeof(struct cstring));
#define NEWCLASS_C calloc(1,sizeof(struct cstring));
struct cstring {
char *c;
};
cstring cstring_new(char *n) {
CLASS i = NEWCLASS;
i->c = strdup(n);
return i;
}
int cstring_length(cstring this) {
return strlen(this->c);
}

Issues:

The current compiler (v0.1) will reject quite some valid C code. Also the given error is not very helpful;

Java::Import is Perl module to use Java classes in Perl.

SYNOPSIS

use Java::Import qw(
some.package.SomeClass
);

my $instance = new some.package.SomeClass();
$instance->someMethod();

my $ret_val = some::package::SomeClass::someStaticMethod();
$ret_val->someMethod();

$ret_val2 = $instance->someOtherMethod($ret_val);
$ret_val2->someMethod();

my $java_array_ref $instance->someMethod2();
foreach my $obj ( @$java_array_ref ) {
$obj->someMethod();
}

The purpose of this module is to provide a simple method for using Java classes from a Perl program while using the latest in Open Source Java Technology. Thus, this module makes great use of the GNU Compiler Tools for Java in its implimentation.

Math::Symbolic::Compiler is a Perl module that can compile Math::Symbolic trees to Perl code.

SYNOPSIS

use Math::Symbolic::Compiler;

# A tree to compile
my $tree = Math::Symbolic->parse_from_string(a^2 + b * c * 2);

# The Math::Symbolic::Variable a will be evaluated to $_[1], etc.
my $vars = [qw(b a c)];

my ($closure, $code, $trees) =
Math::Symbolic::Compiler->compile($tree, $vars);

print $closure->(2, 3, 5); # (b, a, c)
# prints 29 (= 3^2 + 2 * 5 * 2)

# or:
($closure, $trees) =
Math::Symbolic::Compiler->compile_to_sub($tree, $vars);

($code, $trees) = Math::Symbolic::Compiler->compile_to_code($tree, $vars);

This module allows to compile Math::Symbolic trees to Perl code and/or anonymous subroutines whose arguments will be positionally mapped to the variables of the compiled Math::Symbolic tree.

The reason youd want to do this is that evaluating a Math::Symbolic tree to its numeric value is extremely slow. So is compiling, but once youve done all necessary symbolic calculations, you can take advantage of the speed gain of invoking a closure instead of evaluating a tree.