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Software and Systems Modeling

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29-05-2017 | Regular Paper

Assessing the impact of meta-model evolution: a measure and its automotive application

Authors: Darko Durisic, Miroslaw Staron, Matthias Tichy, Jörgen Hansson

Published in: Software and Systems Modeling | Issue 2/2019

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Abstract

Domain-specific meta-models play an important role in the design of large software systems by defining language for the architectural models. Such common modeling languages are particularly important if multiple actors are involved in the development process as they assure interoperability between modeling tools used by different actors. The main objective of this paper is to facilitate the adoption of new domain-specific meta-model versions, or a subset of the new architectural features they support, by the architectural modeling tools used by different actors in the development of large software systems. In order to achieve this objective, we developed a simple measure of meta-model evolution (named NoC—Number of Changes) that captures atomic modification between different versions of the analyzed meta-model. We evaluated the NoC measure on the evolution of the AUTOSAR meta-model, a domain-specific meta-model used in the design of automotive system architectures. The evaluation shows that the measure can be used as an indicator of effort needed to update meta-model-based tools to support different actors in modeling new architectural features. Our detailed results show the impact of 14 new AUTOSAR features on the modeling tools used by the main actors in the automotive development process. We validated our results by finding a significant correlation between the results of the NoC measure and the actual effort needed to support these features in the modeling tools reported by the modeling practitioners from four AUTOSAR tool vendors and the AUTOSAR tooling team at Volvo Cars. Generally, our study shows that quantitative analysis of domain-specific meta-model evolution using a simple measure such as NoC can be used as an indicator of the required updates in the meta-model-based tools that are needed to support new meta-model versions. However, our study also shows that qualitative analysis that may include an inspection of the actual meta-model changes is needed for more accurate assessment.

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OCA uses two dimensions for representing meta-modeling layers, where the ontological instantiation is depicted horizontally (“O” layers) and the linguistic vertically (“L” layers).

Method for calculating meta-model changes related to specific features is presented in [13].

Please note that this may not be true in the general case, e.g., editors of the Eclipse Graphical Modeling Framework rely on the package structure of the domain meta-model.

Note that this exclusion is not part of our NoC definition as it is domain-specific, i.e., other domains may need to configure the NoC measure to exclude some other types of not relevant changes in order to increase the accuracy of the measurement results.

The complete list of excluded meta-model changes and tool mappings can be found here (“ARCA_Config.xml”): https://www.chalmers.se/en/projects/Documents/ARCA.zip

The complete exports from the ARCA tool can be found here (“NoC results (AR421 features)” folder): https://www.chalmers.se/en/projects/Documents/ARCA.zip

We calculated the percentage of the top five features ordered both by the efforts and NoC.

We consider the difference in order to be small if it is less than or equal to 3.

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Title: Assessing the impact of meta-model evolution: a measure and its automotive application
Authors: Darko Durisic
Miroslaw Staron
Matthias Tichy
Jörgen Hansson
Publication date: 29-05-2017
Publisher: Springer Berlin Heidelberg
Published in: Software and Systems Modeling / Issue 2/2019
Print ISSN: 1619-1366
Electronic ISSN: 1619-1374
DOI: https://doi.org/10.1007/s10270-017-0601-1

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