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ЯЗЫК LMPL КАК СРЕДСТВО СИНТЕЗА ПРИКЛАДНЫХ ПРОГРАММНЫХ МОДЕЛЕЙ И МЕТАМОДЕЛЕЙ НА ОСНОВЕ ПРИНЦИПОВ МАТЕМАТИЧЕСКОГО ПРОГРАММИРОВАНИЯ

ЯЗЫК LMPL КАК СРЕДСТВО СИНТЕЗА ПРИКЛАДНЫХ ПРОГРАММНЫХ МОДЕЛЕЙ И МЕТАМОДЕЛЕЙ НА ОСНОВЕ ПРИНЦИПОВ МАТЕМАТИЧЕСКОГО ПРОГРАММИРОВАНИЯ

Abstract

The paper describes the LMPL language developed by the authors as an efficient synthesis means of applied software models and metamodels constructed on the basis of mathematical programming (MP) principles. It differs in an explicit form of declarative representation of MP-models, simplified syntax, presumes automatic constructing and transformation of models, and automatic constructing of resulting diagrams with the possibility to add external software packages. The implementation of LMPL is portable and cross-platform.

Описывается разработанный авторами язык LMPL как эффективное средство синтеза прикладных программных моделей и метамоделей, строящихся на основе принципов математического программирования (МП). Он отличается наглядной формой декларативного представления МП-моделей, упрощенным синтаксисом, предусматривает автоматическое построение и преобразование моделей, а также формирование результирующих диаграмм с возможностью подключения внешних программных пакетов. Реализация LMPL является портабельной и кроссплатформенной.

Keywords

ЯЗЫК LMPL, МОДЕЛИРОВАНИЕ, МЕТАМОДЕЛИРОВАНИЕ, МАТЕМАТИЧЕСКОЕ ПРОГРАММИРОВАНИЕ, АВТОМАТИЧЕСКОЕ ПОСТРОЕНИЕ И ПРЕОБРАЗОВАНИЕ МОДЕЛЕЙ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold