Free machines of mayhem software for linux

State Machine Compiler takes a state machine stored in an .sm file and generates the state pattern classes in nine programming languages.
Its features include default transitions, transition arguments, transition guards, push/pop transitions, and Entry/Exit actions. State Machine Compiler requires Java SE 1.4.1 or better.
Enhancements:
- This release cleans up C# and VB.net debug output using System.Diagnostics.Trace.
- It fixes a number of minor bugs.

C++ Machine Objects class library supports a subset of the UML statechart notation for implementing hierarchical state machines in straight C++, similar in spirit to the GoF "State" design pattern.
The currently supported features are hierarchical states, entry and exit actions, state histories, and state variables.
Installation:
The class library as such does not need to be installed. Just include the header file Macho.hpp to make use of it. Prerequisite however is a C++ compiler with sane support for templates.
Included are the example state machines HelloWorld, Example, Microwave and Test. To make the examples run just compile them in the directory they are in, for example:
# GCC
g++ -o microwave Microwave.cpp
# MSVC7
cl /EHsc Microwave.cpp
I like the GoF "State" design pattern. It enables implementing the important concept of state machines with common programming language features. By utilising only basic language mechanisms it is easy to apply in real-life software development.
Another important property that stems from this simplicity is orthogonality, meaning that the pattern can be combined with other design elements, patterns and idioms in arbitrary ways.
In contrast stand the tool supported approaches to state machine creation (of which there is no shortage). Based on code generators and graphical editors, they tend to generate incomprehensible code and forfeit orthogonality by necessarily being outside the domain of the programming language.
Unfortunately the "State" pattern is limited in scope because it does not allow for hierarchical state machines. This is regrettable because flat state machines tend to become unwieldy when getting bigger, for the sheer number of states they produce.
Hierarchical state machines as defined by the statechart notation alleviate this problem by giving an additional structural element through grouping states into hierarchies.
The "State" pattern in its original form is not capable of modeling state hierarchies. The Macho class library extends the concept with this possibility, while keeping the properties of simplicity (there possible) and tool independence from its inspiration.
Enhancements:
- This release adds the feature of backtracking to previous states by using "Snapshots".

Ragel State Machine Compiler compiles finite state machines from regular languages into executable C/C++/Objective-C code. Ragel state machines can not only recognize byte sequences as regular expression machines do, but can also execute code at arbitrary points in the recognition of a regular language.
Ragel can also be thought of as a finite state transducer compiler where output symbols represent blocks of code that get executed instead of written to the output stream.
When you wish to write down a regular language you start with some simple regular language and build a bigger one using the regular language operators union, concatenation, kleene star, intersection and subtraction.
This is precisely the way you describe to Ragel how to compile your finite state machines. Ragel also understands operators that embed actions into machines and operators that control any non-determinism in machines.
Ragel FSMs are closed under all of Ragels regular language, action specification and priority assignment operators. This property allows arbitrary regular languages to be described. Complexity is limited only by available processing resources.
For example, you can make one machine that picks out specially formatted comments in C code, another machine that builds a list all function declarations and a third that identifies string constants then "or" them all together to make a single machine that performs all of these tasks concurrently and independently on one pass of the input.
Main features:
- Describe arbitrary state machines using regular language operators and/or state tables.
- NFA to DFA conversion.
- Hopcrofts state minimization.
- Embed any number of actions into machines at arbitrary places.
- Control non-determinism using priorities on transitions.
- Visualize output with Graphviz.
- Use byte, double byte or word sized alphabets.
- Generate C/C++/Objective-C code with no dependencies.
- Choose from table or control flow driven output.
Enhancements:
- The documentation and the Ruby code generator were improved.

XML::SAX::Machine is a Perl module that can manage a collection of SAX processors.

SYNOPSIS

## Note: See XML::SAX::Pipeline and XML::SAX::Machines first,
## this is the gory, detailed interface.

use My::SAX::Machines qw( Machine );
use My::SAX::Filter2;
use My::SAX::Filter3;

my $filter3 = My::SAX::Filter3->new;

## A simple pipeline. My::SAX::Filter1 will be autoloaded.
my $m = Machine(
#
# Name => Class/object => handler(s)
#
[ Intake => "My::SAX::Filter1" => "B" ],
[ B => My::SAX::Filter2->new() => "C" ],
[ C => $filter3 => "D" ],
[ D => *STDOUT ],
);

## A parser will be created unless My::SAX::Filter1 can parse_file
$m->parse_file( "foo.revml" );

my $m = Machine(
[ Intake => "My::SAX::Filter1" => qw( Tee ) ],
[ Tee => "XML::Filter::SAXT" => qw( Foo Bar ) ],
[ Foo => "My::SAX::Filter2" => qw( Out1 ) ],
[ Out1 => $log ],
[ Bar => "My::SAX::Filter3" => qw( Exhaust ) ],
);

WARNING: This API is alpha!!! It will be changing.

A generic SAX machine (an instance of XML::SAX::Machine) is a container of SAX processors (referred to as "parts") connected in arbitrary ways.

Each parameter to Machine() (or XML::SAX::Machine-new()>) represents one top level part of the machine. Each part has a name, a processor, and one or more handlers (usually specified by name, as shown in the SYNOPSIS).

Since SAX machines may be passed in as single top level parts, you can also create nested, complex machines ($filter3 in the SYNOPSIS could be a Pipeline, for example).

A SAX machines can act as a normal SAX processors by connecting them to other SAX processors:

my $w = My::Writer->new();
my $m = Machine( ...., { Handler => $w } );
my $g = My::Parser->new( Handler => $w );

Visual Turing Machine project is a program that lets you create Turing machines with a point and click interface instead of using esoteric languages.
You can pack your complex machines into small boxes, and then reuse them as part of a bigger machine. VTM also features an infinite length tape.
Enhancements:
- New features include an n-ary set of symbols, multiple windows (MDI), a huge workspace (10000x10000 pixels) without a memory issue, the ability to edit your own machines, the ability to execute machines n times (where n is undefined), the ability to use expressions (like n+5) to execute machines, the ability to execute machines at desired speeds, statistics to see how many instructions were executed and how much tape was "used", and an easy wasy to translate the program to other languages.

Wake On LAN proxy allows machines behind a gateway/firewall to be woken up. You have a constant connection to the Internet, but you are away from base. All machines except the gateway are powered off while you are away. Remotely you decide you want to access one of your machines. You need to power it up first. For machines with suitable NICs there is the Wake On LAN mechanism. But this doesnt work over the Internet because you would have to route a packet to your internal network. The firewall stops you from doing that, for good reasons. Even if you were able to route a packet, you wouldnt want this information to travel in the clear, otherwise other people who intercept your packets could learn how to turn on your machines remotely too. So you need some kind of authentication and privacy.

Enter Wake On LAN proxy. This runs on your gateway, or on some other machine on the network thats always on, and can be reached from the Internet by port forwarding. You can send a command to it to wake a particular machine and it broadcasts a suitable packet on the internal network.

Joeq is a virtual machine and compiler infrastructure designed to facilitate research in virtual machine technologies such as Just-In-Time and Ahead-Of-Time compilation, advanced garbage collection techniques, distributed computation, sophisticated scheduling algorithms, and advanced run time techniques.
Joeq is entirely implemented in Java, leading to reliability, portability, maintainability, and efficiency. It is also language-independent, so code from any supported language can be seamlessly compiled, linked, and executed -- all dynamically.
Each component of the virtual machine is written to be independent with a general but well-defined interface, making it easy to experiment with new ideas.
Joeq is released as open source software, and is being used as a framework by researchers on five continents on topics ranging from automatic distributed virtual machines to whole-program pointer analysis.
Joeq is a virtual machine and compiler infrastructure designed to be a platform for research in compilation and virtual machine technologies. We had three main goals in designing the system. First and foremost, we wanted the system to be flexible. We are interested in a variety of compiler and virtual machine research topics, and we wanted a system that would not be specific to researching a particular area.
For example, we have interest in both static and dynamic compilation techniques, and in both type-safe and unsafe languages. We wanted a system that would be as open and general as possible, without sacrificing usability or performance.
Second, we wanted the system to be easy to experiment with. As its primary focus is research, it should be straightforward to prototype new ideas in the framework. With this in mind, we tried to make the system as modular as possible, so that each component is easily replaceable. Learning from our experience with Jalapeno, another virtual machine written in Java, we decided to implement the entire system in Java.
This makes it easy to quickly implement and prototype new ideas, and features like garbage collection and exception tracebacks ease debugging and improve productivity. Java, being a dynamic language, is also a good consumer for many of our dynamic compilation techniques; the fact that our dynamic compiler can compile the code of the virtual machine itself means that it can dynamically optimize the virtual machine code with respect to the application that is running on it. Javas object-oriented nature also facilitates modularity of the design and implementation.
Third, we wanted the system to be useful to a wide audience. The fact that the system is written in Java means that much of the system can be used on any platform that has an implementation of a Java virtual machine. The fact that Joeq supports popular input languages like Java, C, C++, Fortran, and even x86 binary code increases the scope of input programs. We released the system on the SourceForge web site as open source under the Library GNU Public License.
It has been picked up by researchers on five continents for various purposes, among them: automatic extraction of component interfaces, static whole-program pointer analysis, context-sensitive call graph construction, automatic distributed computation, versioned type systems for operating systems, sophisticated profiling of applications, advanced dynamic compilation techniques, system checkpointing, anomaly detection, secure execution platforms and autonomous systems. In addition, Joeq is now used as the basis of the Advanced Compilation Techniques class taught at Stanford University.
Joeq supports two modes of operation: native execution and hosted execution. In native execution, the Joeq code runs directly on the hardware. It uses its own run-time routines, thread package, garbage collector, etc. In hosted execution, the Joeq code runs on top of another virtual machine. Operations to access objects are translated into calls into the reflection library of the host virtual machine.
The user code that executes is identical, and only a small amount of functionality involving unsafe operations is not available when running in hosted execution mode. Hosted execution is useful for debugging purposes and when the underlying machine architecture is not yet directly supported by Joeq. We also use hosted execution mode to bootstrap the system and perform checkpointing, a technique for optimizing application startup times.
Joeq system consists of seven major parts:
- Front-end: Handles the loading and parsing of input files, such as Java class files, SUIF files, and binary object files.
- Compiler: A framework for performing analyses and optimizations on code. This includes the intermediate representation (IR) of our compiler.
- Back-end: Converts the compilers intermediate representation into native, executable code. This code can be output to an object file or written into memory to be executed. In addition, it generates metadata about the generated code, such as garbage collection maps and exception handling information.
- Interpreter: Directly interprets the various forms of compiler intermediate representations.
- Memory Manager: Organizes and manages memory. Joeq supports both explicitly-managed and garbage-collected memory.
- Dynamic: Provides profile data to the code analysis and optimization component, makes compilation policy decisions, and drives the dynamic compiler.
- Run-time Support: Provides runtime support for introspection, thread scheduling, synchronization, exception handling, interfacing to external code, and language-specific features such as dynamic type checking.