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 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

GReAT

QVT

MOLA

DSLTrans

ProGReS


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

  • 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

Goal:

Build a repository of design patterns for MT development


Pattern identification

  • Identify & discover recurrent patterns in model transformation

    • Completeness issue (see GoF)

    • Systematic process


Pattern identification

  • Examine a large set of data

    • Academic, Industrial

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

    • Case studies from literature


Pattern identification

  • Discover new patterns

    • Map GoF patterns to MT paradigm

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

    • Be creative!


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

  • 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

Goal:

Define quality attributes & propose framework

where transformations are guaranteed to satisfy these criteria


Quality Criteria Identification

  • Quantifiable attributes

  • Techniques to measure them

  • Techniques to evaluate transformations


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


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


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


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


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


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


Quality Criteria Identification

  • Define quality attributes at coarser level

  • Implement techniques to measure these quality criteria

?


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


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


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

  • 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


HOT for detecting patterns


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


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


Conclusion

  • Quality Criteria

  • Design Patterns meeting criteria

  • Automated assistance for MT development

    Your suggestions are vital!Topics for afternoon discussion?


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