Free differences between software for linux

Test::Differences Perl module contains test strings and data structures and show differences if not ok.

SYNOPSIS

use Test; ## Or use Test::More
use Test::Differences;

eq_or_diff $got, "anbncn", "testing strings";
eq_or_diff @got, [qw( a b c )], "testing arrays";

## Passing options:
eq_or_diff $got, $expected, $name, { context => 300 }; ## options

## Using with DBI-like data structures

use DBI;

... open connection & prepare statement and @expected_... here...

eq_or_diff $sth->fetchall_arrayref, @expected_arrays "testing DBI arrays";
eq_or_diff $sth->fetchall_hashref, @expected_hashes, "testing DBI hashes";

## To force textual or data line numbering (text lines are numbered 1..):
eq_or_diff_text ...;
eq_or_diff_data ...;

subPersistence is an abstract, light-weight yet flexible framework for working with O/R persistence mappers. It provides for independence of a specific O/R mapper such as Hibernate or Castor.
While you can use Hibernate or Castor (or other O/R mappers) directly, coupling your application too tightly to those can be a bad thing. subPersistence makes it easy to switch underlying O/R mappers, thereby decoupling the application layer from those.
It abstracts away differences between the mappers, while still making it possible to use their specific features if needed.
Enhancements:
- This version updates to Java 5 features such as Generics and is the first version to require Hibernate 3.

DBD::Ingres contains a DBI driver for Ingres database systems.

SYNOPSIS

$dbh = DBI->connect("DBI:Ingres:$dbname", $user, $options, {AutoCommit=>0})
$sth = $dbh->prepare($statement)
$sth = $dbh->prepare($statement, {ing_readonly=>1})
$sth->execute
@row = $sth->fetchrow
$sth->finish
$dbh->commit
$dbh->rollback
$dbh->disconnect
...and many more

DBD::Ingres is a database driver for the perl DBI system that allows access to Ingres databases. It is built on top of the standard DBI extension and implements the methods that DBI requires.

This document describes the differences between the "generic" DBD and DBD::Ingres.

Rocks Cluster is a complete "cluster on a CD" solution for x86 and IA64 Red Hat Linux COTS clusters.
Building a Rocks cluster does not require any experience in clustering, yet a cluster architect will find a flexible and programmatic way to redesign the entire software stack just below the surface (appropriately hidden from the majority of users).
Although Rocks includes the tools expected from any clustering software stack (PBS, Maui, GM support, Ganglia, etc), it is unique in its simplicity of installation.
From a hardware component and raw processing power perspective, commodity clusters are phenomenal price/performance compute engines. However, if a scalable ``cluster management strategy is not adopted, the favorable economics of clusters are offset by the additional on-going personnel costs involved to ``care and feed for the machine. The complexity of cluster management (e.g., determining if all nodes have a consistent set of software) often overwhelms part-time cluster administrators, who are usually domain application scientists. When this occurs, machine state is forced to either of two extremes: the cluster is not stable due to configuration problems, or software becomes stale, security holes abound, and known software bugs remain unpatched.
While earlier clustering toolkits expend a great deal of effort (i.e., software) to compare configurations of nodes, Rocks makes complete Operating System (OS) installation on a node the basic management tool. With attention to complete automation of this process, it becomes faster to reinstall all nodes to a known configuration than it is to determine if nodes were out of synchronization in the first place. Unlike a users desktop, the OS on a cluster node is considered to be soft state that can be changed and/or updated rapidly.
This is clearly more heavywieght than the philosophy of configuration management tools [Cfengine] that perform exhaustive examination and parity checking of an installed OS. At first glance, it seems wrong to reinstall the OS when a configuration parameter needs to be changed. Indeed, for a single node this might seem too severe. However, this approach scales exceptionally well, making it a preferred mode for even a modest-sized cluster. Because the OS can be installed from scratch in a short period of time, different (and perhaps incompatible) application-specific configurations can easily be installed on nodes. In addition, this structure insures any upgrade will not interfere with actively running jobs.
One of the key ingredients of Rocks is a robust mechanism to produce customized distributions (with security patches pre-applied) that define the complete set of software for a particular node. A cluster may require several node types including compute nodes, frontend nodes file servers, and monitoring nodes. Each of these roles requires a specialized software set. Within a distribution, different node types are defined with a machine specific Red Hat Kickstart file, made from a Rocks Kickstart Graph.
A Kickstart file is a text-based description of all the software packages and software configuration to be deployed on a node. The Rocks Kickstart Graph is an XML-based tree structure used to define RedHat Kickstart files. By using a graph, Rocks can efficiently define node types without duplicating shared components. Similiar to mammalian species sharing 80% of their genes, Rocks node types share much of their software set. The Rocks Kickstart Graph easily defines the differences between node types without duplicating the description of their similarities. See the Bibliography section for papers that describe the design of this structure in more depth.
By leveraging this installation technology, we can abstract out many of the hardware differences and allow the Kickstart process to autodetect the correct hardware modules to load (e.g., disk subsystem type: SCSI, IDE, integrated RAID adapter; Ethernet interfaces; and high-speed network interfaces). Further, we benefit from the robust and rich support that commercial Linux distributions must have to be viable in todays rapidly advancing marketplace.
Wherever possible, Rocks uses automatic methods to determine configuration differences. Yet, because clusters are unified machines, there are a few services that require ``global knowledge of the machine -- e.g., a listing of all compute nodes for the hosts database and queuing system. Rocks uses an SQL database to store the definitions of these global configurations and then generates database reports to create service-specific configuration files (e.g., DHCP configuration file, /etc/hosts, and PBS nodes file).
Enhancements:
- Rocks v4.3 is released for i386 and x86_64 CPU architectures. New features: Rocks command line - initial release of the Rocks command line which facilitates non-SQL administrative access to the database; PXE First - hosts can now be configured in BIOS with a boot order of CD, PXE, hard disk. Enhancements: based on CentOS 4.5 and all updates as of July 4, 2007; Anaconda installer updated to 10.1.1.63; performance improvement when building torrent files for the Avalanche Installer; database indirects, more flexibility with Rocks variables; Globus updated to gt4.0.4 with web services....

REminiscence is a rewrite of the engine used in the game Flashback from Delphine Software.

REminiscence is designed as a cross-platform replacement for the original executable and uses the SDL library.

What are the differences between this and the original engine ?

You can save/load the game state at any time and you can also play in fullscreen or windowed mode.