IRIT/INP-ENSEEIHT, ONERA/DTIS, and CNES, Toulouse (FRANCE)
CADP (Construction and Analysis of Distributed Processes)
Managing the evolution of data models is an important topic in MDE
(model driven engineering). Project stakeholders require an easy and
safe, behaviour-preserving technique to update model-based
applications. This is particularly stringent in the context of space
engineering, where data models may involve thousands of concepts
(each one with a number of fields or attributes) and relationships
(each one with a number of properties). Data model evolution is subject
to three requirements: accessibility (access to model concepts should
be preserved after model refactoring), cardinalities (the cardinalities
defining the extensions of the relationships between source model
concepts should be preserved after model refactoring), and knowledge
(the refactoring process can be supported by a knowledge base or
ontology defining possible knowledge equivalences or relationships
between model concepts).
The approach proposed in this work focuses on the accessibility requirement and supports the analysis of models behavior preservation after refactoring. It consists in checking that the APIs (Application Programming Interfaces) of a source data model still hold on the target data model. The approach consists of four steps:
Addressing the problem of model evolution based on model behavior is
promising. Interfaces defined on data models are used to define model
evolution correctness using observational semantics. Relying on LTSs
has three potential advantages: the overall system is often easier to
understand due to the formal and precise nature of the representation
scheme; the behavior of the system can be analyzed using LTS theory
and associated verification tools; and techniques developed for the
comparison of parallel programs can also be applied.
Lynda Ait Oubelli, Yamine Aït Ameur, Judicaël Bedouet,
Benoît Chausserie-Lapree, and Béatrice Larzul.
"Finding Conservative Schema Evolutions by Analysing API Changes".
Proceedings of the 31st International Conference on Software
Engineering and Knowledge Engineering SEKE'2019 (Lisbon, Portugal),
pp. 748-777, KSI Research Inc., July 2019.
Available on-line at: http://ksiresearch.org/seke/seke19paper/seke19paper_132.pdf
or from our FTP site in PDF or PostScript
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|Further remarks:||This case-study, amongst others, is described on the CADP Web site: http://cadp.inria.fr/case-studies|