A Generative Approach to Model Interpreter Evolution

1. Funded by the DARPA Information Exploitation Office (DARPA/IXO), under the Program Composition for Embedded Systems (PCES) program A Generative Approach to Model Interpreter Evolution Jing Zhang, Jeff Gray, and Yuehua Lin {zhangj, gray, liny} @ cis.uab.eduDept. of Computer & Information Sciences University of Alabama at Birmingham http://www.cis.uab.edu/softcom/

2. Meta-model0 Meta-model1 Meta-modeln …… Based on Define Define Define ∆M 1 ∆MM 1 ∆M 2 ∆MM 2 ∆I 1 ∆M n ∆I 2 ∆MM n ∆I n …… Model1 Model0 Modeln Interpret Interpret Interpret Interpreter0 Interpreter1 Interpretern …… Evolution of models and interpreters in terms of meta-model changes ∆MM: The changes made to the meta-models ∆M: The changes reflected in the domain models ∆I: The changes reflected in the model interpreters

3. Example: Old/New Metamodel and model

4. Example: Old/New Interpreter CBuilderAtom *GetStartState( CBuilderModel *StateDiagram) { CBuilderAtom *startstate = null; const CBuilderAtomList *states = StateDiagram->GetAtoms("State"); POSITION pos=states->GetHeadPosition(); while(pos) { CBuilderAtom *st = states->GetNext(pos); CBuilderConnectionList *cons = st->GetInConnections("Transition"); if ( cons == null ) if ( startstate == null) startstate = st; else <<ERROR: more than one state has no InConnections>> } ASSERT ( startstate !=null ); return startstate;} CBuilderAtom *GetStartState( CBuilderModel *StateDiagram) { const CBuilderAtomList *startstates = StateDiagram->GetAtoms("StartState"); ASSERT(startstates->GetCount()==1); CBuilderAtom *startstate = startstates->GetHead(); return startstate; }

5. Technical Challenges • Lack of formally-written model interpreter • Different developers may program interpreters in various ways • Hard to maintain and evolve such subjective realizations of model interpreters • Lack of formal specification for metamodel transformation • Metamodel transformation specifications must include the entire knowledge for the underlying interpreter evolution • ∆MM ∆I • Lack of support for parsing and invasively transforming program source code from higher-level models. ? • Utilize a mature program transformation engine: The Design Maintenance System (DMS)

6. Modeling API Modeling API’ void CComponent::InvokeEx(CBuilder &builder) { Interpreter aInterpreter; CString fileName; char *specFile=new char[fileName.GetLength()]; strcpy(specFile, fileName); …. } void CComponent::InvokeEx(CBuilder &builder) { Interpreter aInterpreter; CString fileName; if(!aInterpreter.selectSpecAspects(fileName)) { return; } … } model model model model Interpreters Interpreters’ Metamodel Metamodel’ Model Xform Specification Models Models’ Model XformEngine Model Interpreter Evolution Architecture (MIEA)

7. DMS rewriting rules for evolving intepreter(1) • Differences of names for any model entities, relationships and attributes rule ChangeName (id:identifier): expression_statement -> expression_statement ="\id -> GetModels(\“State\");" -> "\id -> GetModels(\“StartState\");".

8. DMS rewriting rules for evolving intepreter(2) • Differences of model types rule ChangeModelType (id:identifier): expression_statement -> expression_statement = “\id -> GetAtoms(\“State\”);” -> “\id -> GetModels(\“State\”);”.

9. DMS rewriting rules for evolving intepreter(3) • Differences of attribute types rule ChangeAttrType (): declaration_statement -> declaration _statement = “CString State_Text;” -> “int State_Text;”.

10. Conclusion • Ideal Goal: • Support the (semi)-automation of model interpreter evolution in terms of metamodel changes and modeling API changes • Proposed Solution: • Model Interpreter Evolution Architecture • Obstacles: • Informal model interpreter • Hard to maintain the fidelity mapping of high-level abstract models to the low-level source code • Possible solution approaches to be investigated: • Attach program rewriting rules to the existing model transformation specification • Develop a new high-level specification for model transformation that can generate the rewriting rules • Investigate an intelligent model comparison technique to generate the rules through human interactions

11. Thank You !! Questions ??