Structuring the modeling space and supporting evolution in software product line engineering (bibtex)
by Deepak Dhungana, Paul Grünbacher, Rick Rabiser, Thomas Neumayer
Abstract:
The scale and complexity of product lines means that it is practically infeasible to develop a single model of the entire system, regardless of the languages or notations used. The dynamic nature of real-world systems means that product line models need to evolve continuously to meet new customer requirements and to reflect changes of product line artifacts. To address these challenges, product line engineers need to apply different strategies for structuring the modeling space to ease the creation and maintenance of models. This paper presents an approach that aims at reducing the maintenance effort by organizing product lines as a set of interrelated model fragments defining the variability of particular parts of the system. We provide support to semi-automatically merge fragments into complete product line models. We also provide support to automatically detect inconsistencies between product line artifacts and the models representing these artifacts after changes. Furthermore, our approach supports the co-evolution of models and their respective meta-models. We discuss strategies for structuring the modeling space and show the usefulness of our approach using real-world examples from our ongoing industry collaboration.
Reference:
Structuring the modeling space and supporting evolution in software product line engineering (Deepak Dhungana, Paul Grünbacher, Rick Rabiser, Thomas Neumayer), In Journal of Systems and Software, volume 83, 2010.
Bibtex Entry:
@ARTICLE{Dhungana2010,
  author = {Deepak Dhungana and Paul Grünbacher and Rick Rabiser and Thomas Neumayer},
  title = {Structuring the modeling space and supporting evolution in software
	product line engineering},
  journal = {Journal of Systems and Software},
  year = {2010},
  volume = {83},
  pages = {1108-1122},
  number = {7},
  abstract = {The scale and complexity of product lines means that it is practically
	infeasible to develop a single model of the entire system, regardless
	of the languages or notations used. The dynamic nature of real-world
	systems means that product line models need to evolve continuously
	to meet new customer requirements and to reflect changes of product
	line artifacts. To address these challenges, product line engineers
	need to apply different strategies for structuring the modeling space
	to ease the creation and maintenance of models. This paper presents
	an approach that aims at reducing the maintenance effort by organizing
	product lines as a set of interrelated model fragments defining the
	variability of particular parts of the system. We provide support
	to semi-automatically merge fragments into complete product line
	models. We also provide support to automatically detect inconsistencies
	between product line artifacts and the models representing these
	artifacts after changes. Furthermore, our approach supports the co-evolution
	of models and their respective meta-models. We discuss strategies
	for structuring the modeling space and show the usefulness of our
	approach using real-world examples from our ongoing industry collaboration.},
  doi = {10.1016/j.jss.2010.02.018},
  keywords = {CD Lab ASE}
}
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