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Using structural decomposition and refinements for deep modeling of software architectures

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Abstract

Traditional metamodeling in two levels gets to its limits when model elements of a domain should be described as instances of other model elements. For example in architecture description languages, components may be instances of their component types. Although workarounds to model such instance relations between model elements exist, they require many validation constraints and imply a cumbersome interface. To obtain more elegant metamodels, deep modeling seeks ways to represent non-transitive instantiation chains directly. However, existing concepts cannot be applied in some situations we refer as composite instantiation patterns. Further, these concepts make existing technologies for model transformation and analysis obsolete as these languages have to be adapted. In this paper, we present an approach to realize deep modeling through structural decomposition and refinements that can be implemented as a noninvasive extension to EMOF-like meta-metamodels. As a consequence, existing tools need not be adapted and composite instantiation patterns are fully supported. We validate our concept by creating a deep modeling architecture description language based on the Palladio Component Model and demonstrate its advantages by modeling a synthetic web application. We show that existing tools for incremental model analysis can be reused and manifest several orders of speedup for a synthetic example analysis.

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Notes

  1. The terminology deep modeling was decided on at the MULTI 2014 workshop, and we adopted in this paper.

  2. A level-adjuvant language is a language where modeling levels are explicit. Elements are assigned to fixed levels, and relations between them are restricted based on elements levels.

  3. Feedback can also be provided without incremental validation, but an incremental execution of validation rules makes them much faster and therefore practical for larger models.

  4. Again, we omitted the required interface for the inner database to save space.

  5. Atkinson and others introduced this situation as a paradox for level-blind languages, i.e., languages that do not have an explicit notion of levels [19]. The tooling for PCM currently does not enforce this constraint.

  6. We need to keep a type separate from its set of instances due to axiomatic set theory.

  7. In implementations, \(\bot \) is typically null.

  8. Here, the \(\equiv \) symbol means that the getter function always returns the same element b.

  9. The introduction of racing bikes or professional racing bikes as in the bicycle challenge of the MULTI workshop for us also does not introduce instantiation relationships because professional racing bikes are still vehicles and the “is–a” relationship is transitive and hence a specialization.

  10. We adopt the terminology from .NET here, in the technical space of Java this is called a super type.

  11. This definition is slightly more strict than the original definition by Carvalho and others: First, they considered type systems where a model element may have multiple types and second, even in the case of a single type they would demand the implication only for concrete types a.

  12. In our implementation, categorization and disjoint categorization are equivalent because objects generally have exactly one type.

  13. A consequence of this assignment is the substitution principle: If the provenances are implemented as refinements of base types, then a cockerdoodle would be a valid instance of Poodle (but not vice versa). Whether this is desirable depends on the domain context. One might want to treat a toypoodle as a poodle, but a cockerdoodle probably not.

  14. Sometimes referred to as ref-objects.

  15. Or two references if the refinement of BaseTypes and the relation are specified separately.

  16. Because NMeta supports type extensions and structured primitive types, the inheritance hierarchy in NMeta is slightly different to the one used in Ecore such that there are two classes in between Class and Type, the equivalent of EClassifier. This is due to classes omitted in Fig. 14 since they are outside the scope of this paper.

  17. As an example the reference for the parent classes, called eSuperTypes in Ecore, is called BaseTypes.

  18. This definition is consistent, because a single feature is a structural decomposition of itself.

  19. A problem here is that the class ReferenceConstraint is capable to hold any model elements, since all classes implicitly inherit from ModelElement. However, the validation of the metamodel will fail if the provided model elements do not fit to the chosen reference’s type.

  20. The reason for NMeta to not support derived features is that NMF has no support for generating OCL expressions due to an incompatible code generation infrastructure. However, NMF allows to customize the generated classes without touching the generated code.

  21. An interesting consequence would be that the generated class for an e-bike would not inherit from the generated class for bike but would implement the interface directly.

  22. In .NET, even simple value types such as integers, enumerations or boolean values inherit from a common Object class. However, we consider these inheritance relationships as purely technical and do not represent it in NMeta.

  23. To be consistent, the uniqueness constraint would be enforced only when reading the collection: whenever a clients wants to traverse a unique collection that is decomposed, the collection is assembled and deduplicated before returning to the caller. Enforcing the uniqueness constraint when adding new elements would cause side-effects to the component features.

  24. This restriction is necessary due to the stratification process in the code generation.

  25. When using deep modeling approaches, the term metamodel gets blurred. We use the term metamodel to describe a model that can be instantiated.

  26. .NET allows classes to privately implement an interface, which means that the implementation is not visible from the class API, but only through this interface.

  27. Prototype: http://github.com/georghinkel/DeepModelingDemo, Full implementation by Alexis Bernhard: https://github.com/ghmanager/DeepPCM/, accessed 2 Aug 2017.

  28. At least not in NMF. Other modeling environments more inspired by ontologies where elements do not necessarily have a type at all may support changing the type of an object at any time.

  29. All references in PCM are suffixed with the class name that defines these references which unnecessarily degrades the understandability of the analysis.

  30. There are even methods to optimize over all possible deployments of a system, given a resource environment [27].

  31. https://github.com/georghinkel/DeepModelingDemo.

  32. For the future, we are planning to introduce dynamic proxies that eliminate this limitation.

  33. Except for the bicycle challenge 2017 [12].

  34. NMeta does not support OCL, but one is free to define constraints and analyses separate from the metamodel in C# that makes OCL redundant [31].

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  1. FZI Forschungszentrum Informatik, Haid-und-Neu-Straße 10-14, 76131, Karlsruhe, Germany

    Georg Hinkel

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Communicated by Prof. Colin Atkinson.

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Hinkel, G. Using structural decomposition and refinements for deep modeling of software architectures. Softw Syst Model 18, 2787–2819 (2019). https://doi.org/10.1007/s10270-018-0701-6

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