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

2. Evolution of models and interpreters in terms of meta-model changes
Define
Interpret
Interpretern
Modeln
Meta-modeln
Interpreter0
Model0
Meta-model0
∆M 1
∆MM 1
∆I 1
∆M 2
∆MM 2
∆I 2
∆M n
∆MM n
∆I n ……
Based on
∆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 ∆MM ∆I
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. Model Interpreter Evolution Architecture (MIEA)
Modeling API’
Modeling API
void CComponent::InvokeEx(CBuilder &builder) {
Interpreter aInterpreter;
CString fileName;
char *specFile=new char[fileName.GetLength()];
strcpy(specFile, fileName); …. }
Interpreters’
if(!aInterpreter.selectSpecAspects(fileName)) {
return; } …
Interpreters
Metamodel’
Metamodel
model
Models
Model Xform Engine
Model Xform Specification
Models’

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
Problems:
2 ways: comparison to infer the rules or attach them to model transformation specifications
rule ChangeAttrType (): declaration_statement -> declaration _statement = “CString Text;” -> “int Text;”.

10. Conclusion Ideal Goal: Proposed Solution: Obstacles:
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 ??