Querying and Annotating Model Histories with Time-Aware Patterns

Antonio García-Domínguez, Nelly Bencomo, Juan Marcelo Parra-Ullauri, Luis Hernán García-Paucar

Research output: Chapter in Book/Published conference outputConference publication

Abstract

Models are not static entities: they evolve over time due to changes. Changes may inadvertently and surprisingly violate constraints imposed. Therefore, the models need to be monitored for compliance. On the one hand, in traditional design-time applications, new and evolving requirements impose changes on a model over time. These changes may accidentally break design rules. Further, the growing complexity of the models may need to be tracked for manageability. On the other hand, newer applications use models at runtime; building runtime abstractions that are used to control a system. Adopters of these approaches will need to query the history of the system to check if the models evolved as expected, or to find out the reasons for a particular behavior. Changes over models at runtime are more frequent than changes over design models. To cover these demands, we argue that a flexible and scalable approach for querying the history of the models is needed to study the evolution and for compliance sake. This paper presents a set of extensions to a model query language inspired in the Object Constraint Language (the Epsilon Object Language) for traversing the history of a model, and for making temporal assertions that will allow the elicitation of historic information. As querying long histories may be costly, the paper presents an approach that annotates versions of interest as they are observed, in order to provide efficient recalls in possible future queries. The approach has been implemented in a model indexing tool, and is demonstrated through a case study from the autonomous and self-adaptive systems domain.

Original languageEnglish
Title of host publicationProceedings - 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems, MODELS 2019
EditorsMarouane Kessentini, Tao Yue, Tao Yue, Alexander Pretschner, Sebastian Voss, Loli Burgueno, Loli Burgueno
PublisherIEEE
Pages194-204
Number of pages11
ISBN (Electronic)9781728125350, 978-1-7281-2536-7
ISBN (Print)978-1-7281-2537-4
DOIs
Publication statusPublished - 21 Nov 2019
Event22nd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2019 - Munich, Germany
Duration: 15 Sept 201920 Sept 2019

Conference

Conference22nd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2019
Country/TerritoryGermany
CityMunich
Period15/09/1920/09/19

Keywords

  • model querying
  • model versioning
  • model-indexing
  • scalable model-driven engineering
  • temporal graph databases

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