McGill University Proposal Exam School of Computer Science Ph.D. Candidate in the Modelling, Simulation and Design Lab Eugene Syriani

McGill University

Proposal Exam

School of Computer Science

Ph.D. Candidate in the Modelling, Simulation and Design Lab

A Multi-Paradigm Foundation for Model Transformation

Language Engineering

Eugene Syriani

Multi-Paradigm Foundation for MTL EngineeringProposal Exam

OUTLINE

Context

Thesis

Overview of the Approach

Planning

Conclusion2

3


MODEL-DRIVEN ENGINEERING

Model

Wheel

Transmission

Mechanics of engine

Electric circuits

Security

Speed control

Resistance to snow

System

Meta-Model

represented by

conforms to

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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

M3

M2

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MODEL TRANSFORMATION DEVELOPMENT

Meta-Model of domain

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Generate Modelling Environment

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Transformation Specification

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• Given input model

• Run transformation– Rules

– Unordered, Priority, Layer, Control Flow

• Output– New model

– Modified model

Execution

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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

LHS RHSNAC

Pre-condition Pattern Post-condition Pattern

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MODELLING THE MTL


RAM PROCESS

(quasi-)Automatically generated environment for pattern language

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Input Meta-Model Output Meta-Model

Relax Augment Modify

Customized Pattern Meta-Model

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TRANSFORMATION SPECIFICATIONDomain-Specific Transformation Patterns

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MINIMAL TRANSFORMATION CORE

• Pre-/post- patterns• Matching• Rewriting• Validation of consistent

rule application• Matches manipulation

– Iteration– Roll-back

• Control flow– Choice– Concurrency

• Composition• Common

representation

Features that allow the execution of MTL

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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 languageUML Activity Diagrams, DEVS

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MOTIF-CORE

DEVST-Core

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MOTIF-CORE

DEVST-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?

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

– Support exception handling

Mainly: implementation...

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WHAT IS REMAINING?

1. CD2RDBMS– Using MoTif

2. AntWorld Simulation– Using T-Core & Python

3. PacMan Game– Using MoTif & extended MoTif-Core

4. Aspect Weaving– Using MoTif

... and case studies

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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

Documents

McGill University Proposal Exam School of Computer Science Ph.D. Candidate in the Modelling, Simulation and Design Lab Eugene Syriani