Transcript Systematic Transformation Development

Proposal Exam
Eugene Syriani
Ph.D. Candidate in the Modelling, Simulation and Design Lab
School of Computer Science
McGill University
Proposal Exam
OUTLINE
 Context
 Thesis
 Overview of the Approach
 Planning
 Conclusion
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MODEL-DRIVEN ENGINEERING
Meta-Model
conforms to
Transmission
Model
Security
Wheel
Speed control
Electric
circuits
Resistance to snow
Mechanics
of engine
represented by
System
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MULTI-PARADIGM MODELLING (MPM)
• Multi-formalism
– Domain-specific formalisms
• Multi-abstraction
• Meta-Modelling
• Model Transformation
• Model everything
– Explicitly
– At the most appropriate level of abstraction
– Using the most appropriate formalism
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MODEL TRANSFORMATION
• Manipulate: access & modify operations
• Simulate: execution
• Generate code: compilation
• Translate: into other models
M1
M2
M3
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MODEL TRANSFORMATION DEVELOPMENT
Meta-Model of domain
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MODEL TRANSFORMATION DEVELOPMENT
Generate Modelling Environment
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MODEL TRANSFORMATION DEVELOPMENT
Transformation Specification
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foodLink
ghostLink
1: return
self.LHS.nodeWithLabel(1).score + 1
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MODEL TRANSFORMATION DEVELOPMENT
Execution
• Given input model
• Run transformation
– Rules
– Unordered, Priority, Layer, Control Flow
• Output
– New model
– Modified model
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PROBLEM STATEMENT
• Meta-Modelling: well established
– Language for model specification
– Automatic generation of modelling environments
• Focus on transformations
– Robust theoretical foundation (e.g., graph transformation)
– Plethora of model transformation languages (MTL)
AGG, ATL, AToM3, FUJABA, GReAT, MOFLON, ProGreS, QVT, VMTS, VIATRA2, ...
– Each one provides tremendous value for its domain of expertise
 No interoperability
 Implementation of transformation paradigm is hard-coded
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MY THESIS
• Contribute to the engineering of model transformation languages
– At the foundation level
– Following MPM principles
• Model everything:
– syntax of MTL
– semantics of MTL
• Provide a framework for building MTLs
• Design & implement a new MTL, following MPM principles
– Core algorithms
– Language building blocks
– Formalism
• Focusing on expressiveness of MTL
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SOLUTION
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EXPLICIT MODELLING OF TRANSFORMATIONS
• Consider MTLs as domain-specific languages
• Explicitly model the patterns & the scheduling
NAC
LHS
Pre-condition Pattern
RHS
Post-condition Pattern
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MODELLING THE MTL
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RAM PROCESS
(quasi-)Automatically generated environment for pattern language
Input Meta-Model
Output Meta-Model
Relax Augment Modify
Customized Pattern Meta-Model
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TRANSFORMATION SPECIFICATION
Domain-Specific Transformation Patterns
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MINIMAL TRANSFORMATION CORE
Features that allow the execution of MTL
•
•
•
•
Pre-/post- patterns
Matching
Rewriting
Validation of consistent
rule application
• Matches manipulation
– Iteration
– Roll-back
• Control flow
– Choice
– Concurrency
• Composition
• Common
representation
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T-CORE
• Executable module
• Efficient implementation of the Matcher & the Rewriter
• Combine primitive transformation constructs with “glue language”
– Programming language
SBL, Python
– Modelling language
UML Activity Diagrams, DEVS
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MOTIF-CORE
T-Core
DEVS
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MOTIF-CORE
DEVS
T-Core
MoTif-Core
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MOTIF
Meta-Model
Semantics
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TRANSFORMATION EXCEPTION HANDLING
• Identification & classification
• Modelling of transformation exceptions
• Exception handling specification in the MT itself
– Post-handling control flow
– Propagation mechanism
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MOTIF FRAMEWORK
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PLANNING
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WHAT IS REMAINING?
Mainly: implementation...
1. RAM process
–
Evaluate usability of a completely modelled environment for designing model
transformation
2. T-Core
–
Module based on a model-centric virtual machine
–
Usable with Python & DEVS
–
Efficient Matcher & Rewriter
3. MoTif-Core
–
Compiler to DEVS
4. MoTif Framework
–
Insert in the loop
–
Support higher-order transformations
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Support exception handling
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WHAT IS REMAINING?
... and case studies
1. CD2RDBMS
– Using MoTif
2. AntWorld Simulation
– Using T-Core & Python
3. PacMan Game
– Using MoTif & extended MoTif-Core
4. Aspect Weaving
– Using MoTif
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CONCLUSION
• Novel approach for designing MTLs
• Based on MPM principles
• Three model transformation formalisms
– Primitive building blocks (T-Core)
 Problem-specific pattern language
– Modularly composable, asynchronous, timed transformations (MoTif-Core)
– General purpose transformation (MoTif)
 Performance analyses
 Compare to other model transformation engineering approaches
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