gjrand is a programmer's library for pseudo-random numbers. It includes random number generator testing code and is intended for simulation, games, and "Monte-Carlo" algorithms. It produces pseudo-random numbers of the types: uniform integers, uniform reals, normally distributed reals, binomial, Poisson, integer permutation, chi-squared distribution, "Student" T distribution, and spherical distribution.
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.
ACL2 is a mathematical logic, programming language, and mechanical theorem prover based on the applicative subset of Common Lisp. It is an "industrial-strength" version of the NQTHM or Boyer/Moore theorem prover, and has been used for the formal verification of commercial microprocessors, the Java Virtual Machine, interesting algorithms, and so forth.
Multiplication Station will teach your child to add, subtract, and multiply. It is a multi-user application with a simple admin interface. All parameters are configurable, like grid size and the fonts and colors of number ranges. A countdown timer is used to keep the player's attention focused. A list of high scores is maintained.
Daikon is an implementation of dynamic detection of likely invariants. An invariant is a property (such as "x=2*y+5" or "this.next.prev = this" or "myarray is sorted by <") that holds at a certain point or points in a program. Invariants are often seen in assert statements, documentation, and formal specifications. Invariants can be useful in program understanding and a host of other applications. Daikon runs a program, observes the values that the program computes, and then reports properties that were true over the observed executions. It can detect properties in Java, C, C++, Perl, and IOA programs, in spreadsheet files, and in other data sources.
alph implements and analyzes historical and traditional ciphers and codes, such as polyalphabetic, substitutional, and mixed employing human-reconstructable algorithms. It provides a pipe filter interface in order to encrypt and decrypt block text to achieve transparency. The program is meant to be used in conjunction with external programs that transfer data, resulting in transparent encryption or decryption of information. The program can thus be used as a mail filter, IRC filter, IM filter, and so on.
The Item Response Theory (IRT) library is a set of functions to estimate the items and abilities from the responses of subjects to a questionnaire. The IRT models supported are the logistic model, the nominal response model, the graded response model, and smoothing by penalization and kernel. The project also hosts rirt, a package for the R Project for Statistical Computing, and eirt, an add-in for Excel.
The Distributed Real-time Embedded Analysis Method (DREAM) is a tool and method for the real-time verification and performance estimation of distributed real-time embedded (DRE) systems. It focuses on the practical application of formal verification and timing analysis to real-time middleware.
Multipurpose Versatile Test Harness (MVTH) is a rapid prototyping and testing platform designed for computer vision algorithms. It benefits from the speed and low-level control of the C language while allowing for iterative tweaking and visualization during a running session (similar to Matlab). The end result is a core infrastructure that supports plugins and allows the rapid testing of ideas and comparisons of incremental improvements with results generated during previous plugin reloads. Plugins with machine/computer vision algorithms, image processing routines, and code for using particle filters (a statistical sampling approach) are included.