Challenges for addressing quality factors in model transformation
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Challenges for Addressing Quality Factors in Model Transformation. Eugene Syriani Jeff Gray. Software Engineering Group Department of Computer Science College of Engineering. University of Alabama. Motivation Challenges & Planned Solutions

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Challenges for addressing quality factors in model transformation
Challenges for Addressing Quality Factors inModel Transformation

Eugene SyrianiJeff Gray

Software Engineering Group

Department of Computer Science

College of Engineering

University of Alabama

  • Motivation

  • Challenges & Planned Solutions

    • Elaboration of framework for good practices & their assessment

    • Formal analysis of this framework

    • Application in industrial settings

  • Conclusion

Model transformation statu quo
Model transformation statu quo






What is missing
What is missing?

  • Good practices to design transformations

    • Pragmatics, “intuitions”

    • Design patterns / anti-patterns

  • Assessments of high quality transformations

    • Quality Criteria

    • Evaluation techniques

    • Metrics

What we propose
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

Design pattern cataloging
Design pattern cataloging


Build a repository of design patterns for MT development

Pattern identification
Pattern identification

  • Identify & discover recurrent patterns in model transformation

    • Completeness issue (see GoF)

    • Systematic process

Pattern identification1
Pattern identification

  • Examine a large set of data

    • Academic, Industrial

    • Repositories: ATL transformation zoo, ReMoDD, tool contests, benchmarks

    • Case studies from literature

Pattern identification2
Pattern identification

  • Discover new patterns

    • Map GoF patterns to MT paradigm

      • What does Visitor, Proxy, Composite, etc. mean?

    • Be creative!

Pattern identification caveat
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

Pattern formalism
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

Quality assessment of mt
Quality assessment of MT


Define quality attributes & propose framework

where transformations are guaranteed to satisfy these criteria

Quality criteria identification
Quality Criteria Identification

  • Quantifiable attributes

  • Techniques to measure them

  • Techniques to evaluate transformations


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

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


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


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


Effort needed to modify the transformation to satisfy new requirements or correct deficiencies

  • Model & transformation evolution techniques can be applied

Inspired by ISO 9126


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

Quality criteria identification1
Quality Criteria Identification

  • Define quality attributes at coarser level

  • Implement techniques to measure these quality criteria


V v of transformation patterns
V&V of transformation patterns

How to verify the MT design patternsagainst the quality attributes?

Model Checker


Formal Properties


MT pattern

Domain meta-model

Assisted design of model transformation


Reduce negative impact of model transformationin complex projects

  • Deep knowledge of semantics of transformation language

    • Rule scheduling

    • Attribute/constraint specification

    • Control logic

The ultimate model transformation ide
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

Pattern detection
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

Resolution of ill formed design
Resolution of Ill-Formed Design


Improve non-functional properties of the transformation

  • Detect design patterns in a given transformation that arealmost similar to one from the catalog

Resolution of ill formed design1
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


  • Quality Criteria

  • Design Patterns meeting criteria

  • Automated assistance for MT development

    Your suggestions are vital!Topics for afternoon discussion?