Modelling to Program

Second International Workshop, M2P 2020, Lappeenranta, Finland, March 10–12, 2020, Revised Selected Papers

AvAjantha Dahanayake,Oscar Pastor

Häftad, Engelska, 2021

Del i serien Communications in Computer and Information Science

576 kr

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Beskrivning

This book constitutes revised selected papers from the Second International Workshop on Modelling to Program, M2P 2020, held in Lappeenranta, Finland, in March 2020.The 10 papers presented were thoroughly reviewed and selected from 24 submissions. The papers provide a discussion on novel approaches to programming based on modelling approaches such as model-driven development (MDE, MDA, MDD) and conceptual-model programming and their future developments. The topics of the papers include notions of models that can be understood and used as programs, models-at-runtime, advanced conceptual modelling, conceptual-model programming, modelling foundation, transformation of models to programs, model suites/ensembles for programmers, modelling as the first step to programming and its revisions, advanced model-driven programming and software modernisation, modelling in applications.

Produktinformation

Utgivningsdatum:2021-03-31
Mått:155 x 235 x 14 mm
Vikt:376 g
Format:Häftad
Språk:Engelska
Serie:Communications in Computer and Information Science
Antal sidor:233
Förlag:Springer Nature Switzerland AG
ISBN:9783030726959

Utforska kategorier

Innehållsförteckning

From Models For Programming To Modelling To Program and Towards Models As A Program.- How to Catch a Moonbeam: From Model-Ware to Component-Ware Software Product Engineering.- Models versus Model Descriptions.- Modeling and Implementing of Industrie 4.0 Scenarios.- Agile Generator-Based GUI Modeling for Information Systems.- Formal Model Checking and Transformations of Models Represented in UML with Alloy.- Structurally Recursive Patterns in Data Modeling and their Resolution.- A Models-to-Program Information Systems Engineering Method.- Automating Implementation of Business Logic of Multi Subject-domain IS onthe Base of Machine Learning, Data Programming and Ontology-based Gener-ation of Labeling Functions.- Conceptual Model Reuse for Problem Solving in Subject Domains.- Applying Model-Driven Approach for Data Model Unification.

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