Search Results for "ns2 code with algorithm"

This project has moved to https://github.com/jplevyak/dparser The master on github is the stable. Please pull that for the very latest code. DParser is a scannerless GLR parser generator based on the Tomita algorithm. It is self-hosted and very easy to use. Grammars are written in a natural style of EBNF and regular expressions and support both speculative and final actions.

A general purpose, object-oriented script language that compiles into code for a register based virtual machine. The language is quite similar to object-oriented high-level languages like Java and C#. The library is entirely self-sufficient and ANSI C compliant. It's main purpose is to be embedded in any application to allow automation of that application through scripting. An integrated C++ binding code generator allows you to create bindings for your application's classes in seconds....

AppM Build Automaiton is an open source and automated software application that is used to construct and build projects on different operating systems and using different development environments. General principles of implementation: -Each project must have a Build Project File, containing the necessary information on the construction of the project. For example, a unique name of the project, dependence on other projects and libraries, methods of construction, etc. Thus, the entire...

IronMeta is an implementation of Alessandro Warth's OMeta metaprogramming system in C#. It provides a packrat parser generator that generates parsers for Parsing Expression Grammars that operate on arbitrary streams of objects.

HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages.

MeMo (stands for Meta-Model) is planned as Generic Programming Language & IDE, as flexible & smart as it is possible for computer application, including adjustable syntax, algorithm reduction. Ideally, it has to contain AI for interacting with the user.

A collection of language tools based on recursive adaptive grammars (RAGs), built around a general RAG parsing algorithm.