Specifying process-oriented hypertext for organizational

computin

Improving the programming language translation process via static structure abstraction and algorithmic code transliteration

Fully automated programming language translation has been described as an unrealistic goal, with previous research being limited by a ceiling of 90% successful code translation. The key issues hindering automatic translation efficacy are the: maintainability of the translated constructs; full utilisation of the target language\u27s features; and amount of manual intervention required to complete the translation process. This study has concentrated on demonstrating improvements to the translation process by introducing the programming-language-independent, Unified Modelling Language (UML) and Computer Assisted Software Engineering (CASE) tools to the legacy-system language migration project. UML and CASE tools may be used to abstract the static framework of the source application to reduce the so called opaqueness of the translated constructs, yielding a significantly more maintainable product. The UML and CASE tools also enhance use of the target language features, through forward engineering of the native constructs of the target language during the reproduction of the static framework. Source application algorithmic code translation, performed as a separate process using transliteration, may preserve maximum functionality of the source application after completion of the static structure translation process. Introduction of the UML and CASE tools in conjunction with algorithmic code transliteration offers a reduction of the manual intervention required to complete the translation process

Trends in Programming Languages for Neuroscience Simulations

Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accurately translating ideas into a working simulation. We review long-term trends in the development of programmable simulator interfaces, and examine the benefits of moving from proprietary, domain-specific languages to modern dynamic general-purpose languages, in particular Python, which provide neuroscientists with an interactive and expressive simulation development environment and easy access to state-of-the-art general-purpose tools for scientific computing

Quantum ESPRESSO: a modular and open-source software project for quantum simulations of materials

Quantum ESPRESSO is an integrated suite of computer codes for electronic-structure calculations and materials modeling, based on density-functional theory, plane waves, and pseudopotentials (norm-conserving, ultrasoft, and projector-augmented wave). Quantum ESPRESSO stands for "opEn Source Package for Research in Electronic Structure, Simulation, and Optimization". It is freely available to researchers around the world under the terms of the GNU General Public License. Quantum ESPRESSO builds upon newly-restructured electronic-structure codes that have been developed and tested by some of the original authors of novel electronic-structure algorithms and applied in the last twenty years by some of the leading materials modeling groups worldwide. Innovation and efficiency are still its main focus, with special attention paid to massively-parallel architectures, and a great effort being devoted to user friendliness. Quantum ESPRESSO is evolving towards a distribution of independent and inter-operable codes in the spirit of an open-source project, where researchers active in the field of electronic-structure calculations are encouraged to participate in the project by contributing their own codes or by implementing their own ideas into existing codes.Comment: 36 pages, 5 figures, resubmitted to J.Phys.: Condens. Matte