Alore is an object-oriented programming language with a clean syntax that resembles Python and Lua. It is optionally-typed like Google Dart. It is both a dynamic scripting language and a general-purpose language with static typing. It is aimed at most programming tasks, from short scripts to complex applications. It allows programmers to freely mix static and dynamic typing within a program. It has native threads and a very fast edit-test cycle. Programmers can always bypass type checking and run their programs immediately.
CrashMail II is a Fidonet tosser/scanner with a built-in AreaFix implementation, support for Binkley style outbound (BSO), and message filtering capabilities. It is a fork of Johan Billing's original CrashMail II distribution that introduces a number of fixes (primarily support for running under 64-bit Linux) and a few new features.
Gibbon is a graphical client for playing backgammon online on the First Internet Backgammon Server or servers that use the FIBS protocol. It is platform-independent, using GTK+ for its user interface. It also contains a converter for different match formats. Currently supported are the Smart Game Format, JellyFish, and JavaFIBS.
StaticPython is a statically linked version of the Python 2.x (currently 2.7.1) and Stackless Python 2.x interpreters and their standard modules for 32-bit (i686, i386, x86) Linux, Mac OS X, and FreeBSD systems. It is distributed as single, statically linked 32-bit executable binaries, which contain the Python scripting engine, the interactive interpreter with command editing (readline), the Python debugger (pdb), most standard Python modules (including pure Python modules and C extensions), coroutine support using greenlet, and multithreading support. The binary contains both the pure Python modules and the C extensions, so no additional .py or .so files are needed to run it. It also works in a chroot environment. The binary uses uClibc, so it supports username lookups and DNS lookups as well (without NSS).
Treba is a commandline tool for training, decoding, and calculating with weighted (probabilistic) finite state automata (WFSA/PFSA). Training algorithms include Baum-Welch (EM), Viterbi training, and Baum-Welch augmented with deterministic annealing. Treba is optimized for speed and numerical stability, and training algorithms can be run multi-threaded on hardware with multiple cores/CPUs. Forward, backward, and Viterbi decoding are supported. Automata for training/decoding are read from a text file, or can be generated randomly or with uniform transition probabilities with different topologies (ergodic or fully connected, Bakis or left-to-right, or deterministic). Observations used for training or decoding are read from text files compatible with AT&T finite state tools and OpenFST.