AnallogicA is an application that generates logical tables based on logical propositions. It is possible to compare inverse equivalence or logical values. Results can be saved in text files, CSV format, and an internal format. The program supports up to 15 different variables, which in combination would be more than 32000 possibilities. It shows the replacements done step-by-step during the analysis, a special function for students.

TSPSG is intended to generate and solve "travelling salesman problem" (TSP) tasks. It uses the Branch and Bound method for solving. Its input is a number of cities and a matrix of city-to-city travel costs. The matrix can be populated with random values in a given range (which is useful for generating tasks). The result is an optimal route, its price, step-by-step matrices of solving, and a solving graph. The task can be saved in an internal binary format and opened later. The result can be printed or saved as PDF, HTML, or ODF. TSPSG may be useful for teachers to generate test tasks or just for regular users to solve TSPs. Also, it may be used as an example of using the Branch and Bound method to solve a particular task.

ODE is a high performance library for simulating rigid body dynamics. It is fully featured, stable, mature, and platform independent with an easy-to-use C/C++ API. It has advanced joint types and integrated collision detection with friction. ODE is useful for simulating vehicles, objects in virtual reality environments, and virtual creatures. It is currently used in many computer games, 3D authoring tools, and simulation tools.

SLEEF (SIMD Library for Evaluating Elementary Functions) is a library that facilitates programming with SIMD instructions. It implements the trigonometric functions, inverse trigonometric functions, exponential and logarithmic functions in double precision without table look-ups, scattering from, or gathering into SIMD registers, or conditional branches. This library also includes some functions for evaluation in single precision.

DEDiscover is a workflow-based differential equation modeling software tool for scientists, statisticians, and modelers. Whether you need to do quick simulation, develop sophisticated models, or teach mathematical concepts, DEDiscover combines a powerful computation engine with a user-friendly interface to give you a tool that's better, faster, and easier-to-use.

Accord.NET provides statistical analysis, machine learning, image processing, and computer vision methods for .NET applications. The Accord.NET Framework extends the popular AForge.NET with new features, adding to a more complete environment for scientific computing in .NET.

Hydra Slayer is a Roguelike game focused on one thing: slaying Hydras. It is inspired by mathematical puzzles about brave heroes slaying many-headed beasts. Since each weapon can only cut off a specific number of heads (no more, no less), and then the Hydra regrows some of the lost heads, to defeat each Hydra, you need to find the sequence of attacks which kills it in the least number of wounds. Hydra Slayer also features divisor weapons, blunt weapons to stun heads, missiles, and shields, and a number of other magical items which are unique to this game.

Fuzzy machine learning framework is a library and a GUI front-end for machine learning using intuitionistic fuzzy data. The approach is based on the intuitionistic fuzzy sets and the possibility theory. Further characteristics are fuzzy features and classes; numeric, enumeration features and features based on linguistic variables; user-defined features; derived and evaluated features; classifiers as features for building hierarchical systems; automatic refinement in case of dependent features; incremental learning; fuzzy control language support; object-oriented software design with extensible objects and automatic garbage collection; generic data base support through ODBC; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use.

Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Theano features tight integration with numpy, transparent use of a GPU, efficient symbolic differentiation, speed and stability optimizations, dynamic C code generation, and extensive unit-testing and self-verification. Theano has been powering large-scale computationally intensive scientific investigations since 2007. But it is also approachable enough to be used in the classroom (IFT6266 at the University of Montreal).