Querying and Annotating Model Histories with Time-Aware Patterns
| Autor: | Juan Marcelo Parra-Ullauri, Luis Hernan Garcia-Paucar, Antonio García-Domínguez, Nelly Bencomo |
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| Rok vydání: | 2019 |
| Předmět: |
business.industry
Computer science Object language Control (management) Search engine indexing 020207 software engineering 02 engineering and technology Query language Domain (software engineering) Scalability 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Set (psychology) Software engineering business computer Object Constraint Language computer.programming_language |
| Zdroj: | MoDELS |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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