Challenges for Addressing Quality Factors in Model Transformation

1. Challenges for Addressing Quality Factors inModel Transformation Eugene SyrianiJeff Gray Software Engineering Group Department of Computer Science College of Engineering University of Alabama

2. Motivation • Challenges & Planned Solutions • Elaboration of framework for good practices & their assessment • Formal analysis of this framework • Application in industrial settings • Conclusion

3. Model transformation statu quo GReAT QVT MOLA DSLTrans ProGReS

4. What is missing? • Good practices to design transformations • Pragmatics, “intuitions” • Design patterns / anti-patterns • Assessments of high quality transformations • Quality Criteria • Evaluation techniques • Metrics

5. What we propose • Define quality criteria based on existing transformations • Identify & classify well-founded MT design patterns with proven quality • Support MT engineers by integrating patterns in their designin an automated manner

6. Design pattern cataloging Goal: Build a repository of design patterns for MT development

7. Pattern identification • Identify & discover recurrent patterns in model transformation • Completeness issue (see GoF) • Systematic process

8. Pattern identification • Examine a large set of data • Academic, Industrial • Repositories: ATL transformation zoo, ReMoDD, tool contests, benchmarks • Case studies from literature

9. Pattern identification • Discover new patterns • Map GoF patterns to MT paradigm • What does Visitor, Proxy, Composite, etc. mean? • Be creative!

10. Pattern identification Caveat • General-purpose vs. Domain-specific MT patterns • Copy elements from source to target model • Animate a state-transition modeling language • Language independence • Declarative/imperative, Unidirectional/bi-directional,Implicit/explicit control flow, In-place/out-place/exogenous/endogenous • Application scenarios • Level of granularity • Rule level • Multiple rules may be required to perform single task • Re-usable libraries of transformation snippets • Composition of patterns

11. Pattern formalism • Facilitate understanding, documenting, communicating, and reasoning about the patterns in a standard way • Must be language independent • MOF-like languages • Use of generics/templates • DSL for describing transformations • Syntax: • Concise MT patterns • Canonical form • Semantics • Well-defined formal semantics • Facilitate analysis • Support for higher-order transformation: fully modeled language

12. Quality assessment of MT Goal: Define quality attributes & propose framework where transformations are guaranteed to satisfy these criteria

13. Quality Criteria Identification • Quantifiable attributes • Techniques to measure them • Techniques to evaluate transformations

14. Correctness Degree to which transformation adheres to a set of requirements • Evaluated by V&V techniques • Key is to make use of traceability links in a transformation Inspired by ISO 9126

15. Re-usability Ease of re-using a transformation • Modular composition of transformation units, rules, complete transformations • Modular transformations (MoTif) • Generic transformations (VIATRA) • Higher-order transformations (ATL, AToM3) Inspired by ISO 9126

16. Efficiency Relationship between performance of execution & amount of resources used under specific conditions • Benchmarking • Optimization at implementation level, but also at design level • Ability to handle large models and complex transformations (fan-in/out) Inspired by ISO 9126

17. Reliability Frequency & criticality of a transformation to behave in an unacceptable manner under permissible operating conditions • Security • Fault-tolerance techniques • Exception handling • Usability • Ensure invariant properties Inspired by ISO 9126

18. Maintainability Effort needed to modify the transformation to satisfy new requirements or correct deficiencies • Model & transformation evolution techniques can be applied Inspired by ISO 9126

19. Interoperability Cooperation between a given model transformation and other systems: transformation models & other software • Model composition • Conform to a common standard serialization of models for I/O

20. Quality Criteria Identification • Define quality attributes at coarser level • Implement techniques to measure these quality criteria ?

21. V&V of transformation patterns How to verify the MT design patternsagainst the quality attributes? Model Checker QualityCriteria Formal Properties Result MT pattern Domain meta-model

22. ASSISTED DESIGN OF MODEL TRANSFORMATION Goal: Reduce negative impact of model transformationin complex projects • Deep knowledge of semantics of transformation language • Rule scheduling • Attribute/constraint specification • Control logic

23. The ultimate Model transformation IDE • Detect design patterns based on the pattern catalog during the development of transformations • Detect a non-exact match of a cataloged pattern & propose a resolution to make it compatible with catalog

24. Pattern Detection • Problem: transformations are defined in a declarative way • Hampers maintenance tasks • Techniques to detect MT pattern in a given MT • Stochastic based on design space exploration • V&V techniques to statically analyze MT & derive structural/behavioral correspondences with existing pattern • Or re-use MT techniques to detect patterns

25. HOT for detecting patterns

26. Resolution of Ill-Formed Design Goal: Improve non-functional properties of the transformation • Detect design patterns in a given transformation that arealmost similar to one from the catalog

27. Resolution of Ill-Formed Design • Detect non-exact matches • Stochastic, search-based techniques to detect similarities between fragments of an MT • Search-based • Transformation by demonstration • Advanced IDE that records examples of how to use a design pattern • Evaluation of detection can only be done empirically, by observation

28. Conclusion • Quality Criteria • Design Patterns meeting criteria • Automated assistance for MT development Your suggestions are vital!Topics for afternoon discussion?