Combining Generative and Graph Transformation Techniques for Model Transformation: An Effective Alliance? Shane Sendall Software Modeling & Verification Lab. Computer Science Department University of Geneva Switzerland Shane.Sendall@cui.unige.ch

Shane Sendall, CUI, University of Geneva Overview Model Transformation Overview of Gmorph Graph Transformation/Generative Programming Closing Remarks Don’t treat language features in a systematic nor thorough way Defer any discussion of GP and GT until example: I assume some familiarity 2 December 2018 Shane Sendall, CUI, University of Geneva

Model Transformation—What A model transformation applies one or more rules according to the presence of certain patterns of elements in the set of source models, resulting in a set of target models. The application of a rule results in any number of the following: the creation of a new model fragment the deletion of an existing model fragment the modification of an existing model fragment (where model fragment is any thing from a model to a model element) In the context of MDA, model transformation can be categorized as: language translation and model evolution 2 December 2018 Shane Sendall, CUI, University of Geneva

Genermorphous (Gmorph) Gmorph is a language (still under development) for specifying and executing model transformations Goal: push imperative approach toward some advantages of declarative approaches, such as, pattern matching, rule application, etc. Context: an experimental language that is not “fully featured”; it does not address all aspects that are useful for mainstream model transformation, e.g., reuse mechanisms, well-formedness checks, concurrent application of rules, etc. 2 December 2018 Shane Sendall, CUI, University of Geneva

Genermorphous (Gmorph) A hybrid approach that offers a (partially) visual transformation language, which address both model evolution and translation categories: Rule Specification language (mixture of Graph Transformation Rules and Generative Programming Principles) Rule Composition language (small imperative language: choice, sequence, iteration) Relation to QVT: results from Gmorph could be fed back into a QVT language 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva Graph Transformation  Graph Rewriting LHS (graph) = left-hand side of rule = pattern RHS (graph) = right-hand side of rule = pattern (Interface = intersection of LHS & RHS) Steps taken in applying a rule match, remove, glue, embed C E D A C B D RHS LHS 2 December 2018 Shane Sendall, CUI, University of Geneva

GT: relevance to Gmorph LHS and RHS Give a ‘before’ and ‘after’ view of rule application For model evolution transformations: rule is a graph rewrite 2 December 2018 Shane Sendall, CUI, University of Geneva

Generative Programming A generative programming consists of three parts: a problem space, a solution space, and the configuration knowledge. Problem space defines the appropriate domain-specific concepts and features. Solution space defines the target model elements that can be generated and all possible variations. Configuration knowledge specifies illegal feature combinations, default settings, default dependencies, construction rules, and optimization rules. 2 December 2018 Shane Sendall, CUI, University of Geneva

GP: relevance to Gmorph Ability to handle variations in source model element matching and target model generation (language translation) Parameterization and “open-world” model of matching Default and configuration information are part of specification 2 December 2018 Shane Sendall, CUI, University of Geneva

Closing Remarks and Future Directions Issues Pattern matching at instance level Optional and multiple matches Transitive closure and sequence of matches Ability to easily define mappings between instances: Current approach: 1-to-1, 1-to-many, many-to-1 by traversal of LHS Interesting alternative: an attribute grammar-like approach, which implicitly traverses LHS 2 December 2018 Shane Sendall, CUI, University of Geneva

Closing Remarks and Future Directions Issues Reversing transformations and model updating (round-tripping) => (persistent) relations Separation between rule language and rule composition language => to be fine-tuned with usage A concrete syntax that doesn’t distort the concrete syntax of source model too much (work back from metamodel instance view) 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva Example using Gmorph Problem: Transform a Java package and its contained abstract classes to a UML package and UML classes that correspond to these Java classes. 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva LHS of Gmorph Rule Spec Metamodel: JavaNB javaP: JavaPackage /javaPackage X, 0..* /classes 0..* /JC: JavaClass /declaredBy /JF: Field /features Additional Selection Conditions: context JC ensure: self.isInterface = false and -- JC classes must not be interfaces self.modifier = ModifierKind::abstract -- JC classes must be abstract Model element instance level 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva RHS of Gmorph Rule Spec Metamodel: UML umlP: Package /ownedMember A, 0..* /owningPackage 0..* /UC: Class /ownedAttribute /AT: Attribute /class Model element instance level 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva RHS of Gmorph Rule Spec Metamodel: UML <umlP> <UC> {A, 0..*} <AT> {0..*} Model element instance level 2 December 2018 Shane Sendall, CUI, University of Geneva

LHS/RHS of Gmorph Rule Spec Metamodel: JavaNB Metamodel: UML umlP: Package javaP: JavaPackage /javaPackage /ownedMember X, 0..* A, 0..* /classes 0..* /owningPackage 0..* /JC: JavaClass /declaredBy /JF: Field /UC: Class /ownedAttribute /AT: Attribute /features /class Additional Selection Conditions: context JC ensure: self.isInterface = false and -- JC classes must not be interfaces self.modifier = ModifierKind::abstract -- JC classes must be abstract Model element instance level 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva Gmorph Rule Script Transform Rule: JavaNB-to-UML_PackageMapping (in javaP: JavaNB::Package, out umlP: UML::Package) Instance Mapping: javaP --> umlP; mapeach x in X onto a in A { x.JC --> a.UC; mapeach srcField in x.JC.features onto tgtAttr in a.ownedAttribute { srcField --> tgtAttr; } Type Mapping: UML::Package <-> JavaNB::Package { } UML::Class <-> JavaNB::JavaClass { LHS.name <-> RHS.simpleName | LHS.isRoot <- RHS.superClassName.size() = 0 | … 2 December 2018 Shane Sendall, CUI, University of Geneva

Gmorph Rule Script (cont’d) -- Type Mapping (cont’d) UML::Attribute <-> JavaNB::Field { LHS.name <-> RHS.name | LHS.scope <-> RHS.scope | LHS.visibility <-> RHS.visibility | false -> RHS.isVolatile | LHS.isDerived <- false | … } UML::VisibilityKind <-> JavaNB::VisibilityKind { LHS.vk_public <-> RHS.public | LHS.vk_protected <-> RHS.protected | LHS.vk_private <-> RHS.private | LHS.vk_package <-> RHS.package 2 December 2018 Shane Sendall, CUI, University of Geneva

Closing Remarks and Future Directions Advantages of Gmorph cognitive and practical advantages for concrete syntax approach (WYSIWYG) and explicit LHS and RHS (the before and after transformation view) Patterns described as object structures works well with “imperative” style traversal 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva Other Approaches IBM/DSTC QVT (logic language) Reversibility (due to unification) Usability, Performance? QVTP (relation-based approach) Nice expression of 1-to-1 language translation Awkward for complex model evolution trans.? Sun/Compuware QVT (logic language?) Reversibility, modularity Feasibility of using OCL to fully describe LHS/RHS? UMLX Graphical notation based on Graph Transformation Feasibility of encoding complex trans. graphically? Language translation transformations? 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva Matching Features Additional Features Optional matches for one or more p-elements p-element/group of p-elements are optionally matched (matching is mandatory by default) Maximum possible number of p-element matches are made Multiple matches for one or more p-elements Collection of tuples (tuple of p-elements scoped by matching container) Transitive closure matches for one or more p-elements Collection of tuples Fixpoint iteration Sequence of matches for one or more p-elements Sequence of tuples Ordered according to specified criteria 2 December 2018 Shane Sendall, CUI, University of Geneva

OMG’s Model Driven Architecture Initiative Three levels: Platform Independent Model(s) Platform Specific Model(s) Code & Deployment/Configuration Information The big issues in automation support for MDA: Consistency and synchronization between levels (vertical and horizontal) Support in construction tasks MOF 2.0 Query/View/Transformation Standardization The important point is parameterized transformations and synchronization between and within levels 2 December 2018 Shane Sendall, CUI, University of Geneva

Model Transformation—Why Categories: Model Translation inter-model mapping, synthesis, splitting, and updating Model Evolution source model is target model (same/copy) Examples in MDA: Model Synchronization, Refinement, and Forward and Reverse Engineering PIM We can determine two main categories of transformation in MDA PSM PSM 2 December 2018 Shane Sendall, CUI, University of Geneva

Model Transformation—Why Examples (cont’d) Synthesis of views E.g., bringing together the protocol view with the operation view to form the behavior model Generation of Views E.g., generating a scenario from a statemachine Application of Software Patterns and Refactoring E.g., applying the Singleton design pattern to a design model Protocol View UML State Diagram UML Sequence Diagram Behavior Model Operation View 2 December 2018 Shane Sendall, CUI, University of Geneva

Model Transformation—How Declarative approaches Logic languages Graph Rewriting languages Relation/Mapping languages Imperative, direct model manipulation approaches <your favorite mainstream language> + API to model repository of tool XML-based approaches XSLT (and co.)/XMI.difference (XMI -> XMI) Generative approaches Template/Frame languages Transformation generator languages Hybrid approaches Mix declarative and imperative styles 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva Graph Transformation  Graph Rewriting LHS (graph) = left-hand side of rule = pattern RHS (graph) = right-hand side of rule = pattern (Interface = intersection of LHS & RHS) Steps taken in applying a rule match, remove, glue, embed C E D A C B D RHS LHS 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva Graph Transformation Issues Dangling Edges Commutativity of rules Triggering Conditions Embedding rules Efficient algorithms for LHS matching Reversibility of rules (RHS  LHS) 2 December 2018 Shane Sendall, CUI, University of Geneva

Shane Sendall, CUI, University of Geneva JavaNB Metamodel 2 December 2018 Shane Sendall, CUI, University of Geneva