Model-Based Software and Systems Engineering

12th International Conference, MODELSWARD 2024, Rome, Italy, February 21–23, 2024, Revised Selected Papers

AvFrancisco José Domínguez Mayo,Luís Ferreira Pires

Häftad, Engelska, 2025

Del 2547 i serien Communications in Computer and Information Science

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Beskrivning

This volume constitutes the revised selected papers of 12th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2024, in Rome, Italy, during February 21–23, 2024.The 7 full papers and 6 short papers included in this book were carefully reviewed and selected from 47 submissions. The papers are categorized under the topical sections as follows: Methodologies, Processes and Platforms; Modeling Languages, Tools and Architectures.

Produktinformation

Utgivningsdatum:2025-08-21
Mått:155 x 235 x 16 mm
Vikt:435 g
Format:Häftad
Språk:Engelska
Serie:Communications in Computer and Information Science
Antal sidor:270
Förlag:Springer International Publishing AG
ISBN:9783031968402

Utforska kategorier

Programvaruutveckling inom Data och IT
Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT

Innehållsförteckning

.- Methodologies, Processes and Platforms..- A Framework for Comparative Analysis of News Content: A Model-Based Approach..- Analyzing Side-Tracking of Developers Using Object-Centric Process Mining..- Enhancing Scenario-Based Modeling Using Large Language Models..- Model-Driven Development of Chatbot Microservices..- DynaTool: A Tool for Optimizing Hybrid Software Process..- Modeling Languages, Tools and Architectures..- Specifying, Analysing and Implementing Decision-Support System Architectures..- An Approach for the Comparative Evaluation of RequirementsFormalisation Approaches..- A Pluggable Type Checker for Representing Kinds of Quantities..- Model-Driven Engineering for Data Provenance: A Graphical W3C PROV Modeling Tool..- LLM as a Code Generator in Agile Model Driven Development..- A Modeling Framework for Hardware-Software Systems with Machine Learning Components..- Code Generation for Smart Contracts in Enterprise Application Integration..- Deploying Machine Learning for Automatic Metamodel Instance Generation.