Automating Activities in MDE Tools

Miguel Andrés Gamboa, Miguel Andrés Gamboa, Eugene Syriani, Eugene Syriani

Abstract

Model-Driven Engineering (MDE) is a victim of its own success: being able to quickly generate software tools, many modeling tools exist today, but their usability is far from efficient. Complex processes and repetitive tasks are often required to perform a modeling activity, such as creating a domain-specific language or creating a domain-specific model. The goal of this paper is to increase the productivity of modelers in their every day activities by automating the tasks they perform in current MDE tools. We propose an MDE-based solution where the user defines a workflow that can be parametrized at run-time and executed. Our solution works for frameworks that support two level metamodeling as well as deep metamodeling. We implemented our solution in the MDE tool AToMPM. We also performed a preliminary empirical evaluation of our approach and showed that we reduce both mechanical and cognitive efforts of the user.

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Paper Citation


in Harvard Style

Gamboa M. and Syriani E. (2016). Automating Activities in MDE Tools . In Proceedings of the 4th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD, ISBN 978-989-758-168-7, pages 123-133. DOI: 10.5220/0005760701230133


in Bibtex Style

@conference{modelsward16,
author={Miguel Andrés Gamboa and Eugene Syriani},
title={Automating Activities in MDE Tools},
booktitle={Proceedings of the 4th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD,},
year={2016},
pages={123-133},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005760701230133},
isbn={978-989-758-168-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD,
TI - Automating Activities in MDE Tools
SN - 978-989-758-168-7
AU - Gamboa M.
AU - Syriani E.
PY - 2016
SP - 123
EP - 133
DO - 10.5220/0005760701230133