Unifying Approach for Model Transformations in the MOF Architecture

1. Unifying Approach for Model Transformations in the MOF Architecture Ivan Kurtev, Klaas van den Berg University of Twente, the Netherlands

2. Outline • Transformation scenarios; • Limitations in current transformation languages; • Uniform representation of model elements in MOF; • Transformation language; • Instantiation mechanisms; • Conclusions;

3. Transformation Scenarios (1) Data Transformation Scenario • Transformation is executed over concrete data instances at level M0; • E.g. Common Warehousing Metamodel (CWM); QVT Scenario • Transformation specified between meta models; • The context of Query/Views/Transformation RFP by OMG;

4. Transformation Scenarios (2) Data Binding in context of MOF • Transformation specified at level M2 is executed twice in lower levels M1 and M0; Inter-level Transformations • XML Metadata Interchange (XMI); • Java Metadata Interchange (JMI);

5. Transformation Techniques (1) • QVT Scenario: • 5 submissions to OMG, standardization is expected; • Data transformation Scenario: • CWM OMG document; • Supports object-oriented, relational, XML, record-based data sources; • Data Binding: • proprietary tools, outside the context of MOF architecture; • XMI, JMI: • transformations specified with grammars and templates; • There is no single language that addresses all the scenarios. • QVT and CWM languages have similarities but cannot be applied in a different context.

6. Transformation Techniques (2) QVT Languages: • Execute transformations among models at level M1; • Rely on the MOF instantiation mechanism: • Non-abstract Classifiers at level M2 can be instantiated; • Attributes become slots; • Associations become links; • Instantiation for models at M1 is not defined by MOF; Disadvantages: • QVT languages are not applicable at level M0; • Coupled with the MOF instantiation;

7. Transformation Techniques (3) Common Warehouse Metamodel (CWM): • Reuses the concepts of classes and instances from UML; • Concrete data models (XML, Relational,…) specialize these concepts; • To apply CWM transformations we extend CWM meta model; Disadvantages: • Can not handle models at level M2 if they do not specialize CWM;

8. Transformation Techniques (4) Summary • Current transformation languages are coupled with particular instantiation mechanisms • This coupling prevents the existence of a single transformation language for all scenarios Problem • How to unify the different transformation techniques?

9. Approach Two basic ideas: • Represent model elements at any level of MOF in a uniform way; • Decouple the transformation language from instantiation mechanism; Single GenericRepresentation Transformation Language: • Operates on the generic representation; • Specifies different instantiation mechanisms as transformations;

10. Structure of Model Elements • MOF architecture is a space of model elements; • Elements have identity and named slots; • Special instanceOf slots; • This structure is applicable to model elements at any level of the MOF architecture; • Slot multiplicity is not modeled;

11. Example: MOF Model Representation (1) Simplified MOF Model Primitive data types and multiplicity are skipped

12. Example: MOF Model Representation (2) MOF Model represented as a set of model elements

13. Example: MOF Model Representation (2) MOF Model represented as a set of model elements

14. Multiple InstanceOf Relations • InstanceOfMOF – linguistic (physical) instantiation; • InstanceOfJava – ontological (logical) instantiation;

15. Example: Relational Model (1) Metamodel of relational schemas and its instances

16. Example: Relational Model (2) Two ways to refer to the field A: • Navigating over the graph: aTuple.field[name=“A”].value • By using the type aSchema: aTuple.A • The first is linguistic, based on InstanceOfMOF; • The second is ontological, based on InstanceOfREL;

17. Transformation Language • Models are sets of model elements; • Transformations are set of rules; • Two types of rules: • Model element rule: creates model elements in the target model; • Slot rules: assign values to slots; • Four basic operations: • Selection of source model elements on the base of their type; • Instantiating model elements on the base of a type; • Accessing slot values; • Assigning values to slots;

18. Modeling Instantiation • InstanceOfMOF is assumed to be default instantiation mechanism; • Possibility to work with any other ontological instantiation mechanism; • Transformation engine is configured with: • Rules for instantiation; • Rules for slot access; • Rules for assigning values to slots;

19. Instantiating Model Elements (1) • Instantiation is treated as a transformation from a model element (the type) to another model element (instance) with empty slots; • Instantiation is defined in the transformation language; Example: MOF Instantiation (the default mechanism): MOFAttributeToSlot ModelElementRule source [a:Attribute] target [Slot {name=a.name}] MOFAssociationToSlot ModelElementRule source [assoc:Association] target [Slot {name=assoc.to.name}] MOFClassInstantiation ModelElementRule source [c:Class, condition {c.isAbstract=false}] target [ModelElement {slots}] SlotRules { attributeSlots source [a:Attribute=c.attributes] target [slots] associationSlots source [assoc:Association, condition {assoc.from.type=c}] target [slots] }

20. Instantiating Model Elements (2) Relational schema instantiation: RelSchemaInstantiation ModelElementRule source [s:RelationalSchema] target [Tuple{field, instanceOfRel =s}] SlotRules{ Fields source [f:FieldType=s.fieldTypes] target [field] } FieldTypeToField ModelElementRule source [ft:FieldType] target [Field{name=ft.name}] Instantiation of Tuple and Field is according to the default MOF instantiation

21. Accessing Slot Values • Two options: • Slot exists in the underlying representation: Example: slot named field of aTuple model element; • Slot does not exist. Example: slots A and B of aTuple model element; • In the second case we model slot access as a slot rule: • TupleFieldToSchemaField SlotRule inputParameters [slotName: String, contextNode:Tuple] • source [f:Field=contextNode.field, condition{f.name=slotName}] • target [Slot{name=slotName}=f.value]

22. Assigning Slot Values • The same two options: • Slot exists in the underlying representation Example: slot named field of aTuple model element; • Slot does not exist (It is a logical one); Example: slots A and B of aTuple model element; • In the second case we model the setting of the value as in-place transformation: • SettingSlotValue ModelElementRule • inputParameters [slotName:String, newValue:ModelElement] • source [s:Tuple, f:Field=s.field, condition {f.name=slotName}] • target [update f {value=newValue}]

23. Conclusions • Transformation language: • Transformations between models at any level in MOF; • Decoupled from the instantiation mechanism; • Different instantiations are modeled as generic transformations; • Future Work: • Modeling Generalization relation;