Vol-1652
urn:nbn:de:0074-1652-4

Copyright © 2016 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors.

BigMDE 2016
Scalable Model Driven Engineering

Proceedings of the 4rd Workshop on Scalable Model Driven Engineering
part of the Software Technologies: Applications and Foundations (STAF 2016) federation of conferences

Vienna, Austria, July 8, 2016.

Edited by

Dimitris Kolovos *
Davide Di Ruscio
Nicholas Matragkas *
Jesús Sánchez Cuadrado **
Istvan Rath *
Massimo Tisi ****

* University of York, Department of Computer Science, United Kingdom
** Univeristy of L'Aquila, Department of Information Engineering Computer Science and Mathematics, Italy
*** University of Hull, Department of Computer Science, United Kingdom
**** Universidad Autónoma de Madrid, Computer Science Department, Spain
***** Budapest University of Technology and Economics, Department of Measurement and Information Systems, Hungary
****** Ecole des Mines de Nantes , Department of Computer Science, France

Table of Contents

Preface

Towards Flexible Model Analysis and Constraint Development: A Small Demo Based on Large Real-Life Data 1-10
Matthias Sedlmeier, Martin Gogolla
Evaluation of Model Comparison for Delta-Compression in Model Persistence 11-20
Matthias Scheidgen
Scalability of Model Transformations: Position Paper and Benchmark Set 21-30
Daniel Strüber, Timo Kehrer, Thorsten Arendt, Christopher Pietsch, Dennis Reuling
Managing Model and Meta-Model Components with Export and Import Interfaces 31-36
Daniel Strüber, Stefan Jurack, Tim Schäfer, Stefan Schulz, Gabriele Taentzer
Model-driven Video Decoding: An Application Domain for Model Transformations 37-46
Christian Schenk, Sonja Schimmler, Uwe M. Borghoff
Optimized Declarative Transformation: First Eclipse QVTc Results 47-56
Edward D. Willink

The whole proceedings can also be downloaded as a single file (ZIP).

2016-08-29: submitted by Jesús Sánchez Cuadrado, metadata incl. bibliographic data published under Creative Commons CC0
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