GluCat is a library of template classes that model the universal Clifford algebras over the field of real numbers, with arbitrary dimension and arbitrary signature. It implements a model of each Clifford algebra corresponding to each non-degenerate quadratic form up to a maximum set by the user. GluCat classes are designed to be used as template parameters for other template libraries. GluCat includes the PyClical extension module for Python. This implements the Python classes index_set and clifford, which interface to corresponding C++ classes in GluCat.
Wintermute is an intelligent framework of applications and libraries that uses neural networking to learn about its host. A pseudo-langauge engine that permits translations and grammar rulesets of any language to be incorporated into the system, and database downloads of different sets of data combine to provide a virtual self-thinking assistant that can be used to perform tasks like dictation to a text editor, and more complex tasks such as sorting of documents depending on the time of day, or automation of other routine tasks. It should be noted that Wintermute itself is a meta-project. It encompasses a large array of currently existing and potential produced projects.
Assignment Collector/Grader is a Web application for collecting and automatically grading student lab work. It automatically runs JUnit tests against student uploads, immediately provides feedback to students, records student results for later review, provides a gradesheet summary of student performance, allows easy administration of students, assignments, and classes, and allows the availability of an Assignment to be timed.
Ramona is an enterprise-grade runtime supervisor that allows software programs to be controlled and monitored during their execution life cycle. It provides supervisor/console functionality with init.d-like start/stop control, continuous integration (e.g. unit/functional/performance test launcher), deployment automation, and other command-line oriented features.
Metrix++ is a platform to collect and analyze code metrics. It has a plugin-based architecture, so it is easy to add support for new languages, define new metrics, and/or create new pre- and post-processing tools. Every metric has 'turn-on' and other configuration options. There are no predefined thresholds for metrics or rules; you can choose and configure any limit you want. It scales well to large codebases. For example, initial parsing of about 10000 files takes 2-3 minutes on an average PC, and only 10-20 seconds for iterative re-run. Reporting summary results and exceeded limits takes less than 1 - 10 seconds. It can compare results for 2 code snapshots (collections) and differentiate added regions (classes, functions, etc.), modified regions, and unchanged regions. As a result, easy deployment is guaranteed into legacy software, helping you to deal with legacy code efficiently, and either enforce the 'leave it not worse than it was before' rule or motivate re-factoring.