The fstrcmp library provides an fstrcmp function that returns a number between 0.0 (nothing alike) and 1.0 (identical); this can be used to suggest likely alternatives in error messages. Fuzzy comparisons for byte arrays, wide character strings, and multi-byte character strings are also available. In addition, there are integer alternatives for systems with slow floating point emulation.
The minfx project is a Python package for numerical optimization. It provides a large collection of standard minimization algorithms, including the line search methods (steepest descent, back-and-forth coordinate descent, quasi-Newton BFGS, Newton, and Newton-CG), the trust-region methods (Cauchy point, dogleg, CG-Steihaug, and exact trust region), the conjugate gradient methods (Fletcher-Reeves, Polak-Ribiere, Polak-Ribiere +, and Hestenes-Stiefel), the miscellaneous methods (Grid search, Simplex, and Levenberg-Marquardt), and the augmented function constraint algorithms (logarithmic barrier and method of multipliers).
o42a is a high-level general purpose programming language. It is compiled, statically-typed, prototype-based, logic-driven, and primarily declarative, while the imperative programming style is also supported. A program written in o42a is closer to natural English text than one written in any C-like programming language. The language is designed with programming productivity and code maintainability as main priorities. This achieved by powerful, yet restrained, semantics, and expressive and natural syntax.
ted (Tiny EDitor) is a lightweight commandline text editor designed for scripting. It's intended to be an easier-to-use alternative to "ed". It is lightweight, scriptable, and easily harnessed by shell scripts, but doesn't suffer from the chronic user-unfriendliness that characterizes ed. It is also slightly more featureful than ed, and includes multiple editing buffers and built-in script handling.
Tomld (tomoyo learning daemon) is an extension to the Tomoyo security framework. Tomoyo increases security by confining applications and services into domains using rules. Tomld automates this process, helping users harden their systems more easily. To do this, tomld starts in learning mode, creates Tomoyo domains, collects rules, changes them, and, once the rules appear to be complete, tomld enforces the policy.