MDA_0507Notes

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Agent-Oriented Software Engineering Model Transformations

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Example 3: Metamodel for Jack agents

Example #3: Metamodel for BDI agents.

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Partial view of JACK metamodel

In the design of a multiagent systems (MAS) we can distinguish models thatdescribe the entities at the MAS level and models that describe the internal

structure and/or the behaviour of individual agents. At the MAS we find conceptslike teams, agents, roles, events, and plans. At the level of individual agents we

find the same concepts again (note that teams can be viewed as individualagents and vice versa), where events and plans are described in much moredetail, and additional concepts like capabilities and belief data. The figuredisplays the metamodel for BDI agents in JDE when the system is used in themore general team mode. Teams are formed by groups of agents but may alsoconsist of only a single agent. The metamodel explains how the basic conceptsrelate to each other.

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Foundations of model mappings andtransformations

Foundations of model mappings and transformations.

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Model mapping & transformation

Definition: A model transformation is a mapping of a setof models onto another set of models or ontothemselves, where a mapping defines correspondencesbetween elements in the source and target metamodels.

Correspondence of elements can be

1-to-1, n-to-1, 1-to-n or n-to-n

Mapping is performed at design time

Mapping is defined with models one meta-level higherthan the input and output of the transformation

Mapping describes the rules used for the transformation

Transformation is used at run-time

Mapping is performed by defining relations between two models. The

relations can be 1-to-1, n-to-1, 1-to-n or n-to-n. Mapping is performed in

design time.

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Mapping function

Mb: Model of b

f : Mapping function

Ma: Model of a

MMb: Metamodel of b

MMa: Metamodel of a

Mb f (MMa, MMb, Ma)

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Mapping and transformation

SourceMetamodel

InputModel

OutputModel

TargetMetamodel

Mapping

Transformation

based on

This figure illustrates the mapping as we have already explained.

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Mappings on different abstraction levels

PSM1metamodel

PSM2metamodel

PIM2metamodel

PIM1metamodel

HorizontalMapping

Horizontal

Mapping

Vertical Mapping Vertical Mapping

HighAbstraction

LowAbstraction

We can map between models that are on the same abstraction level

illustrated with horizontal mapping, or we can map between abstraction

levels illustrated with vertical mapping in the figure.

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Model transformation technologies andexamples

Model transformation technologies and examples.

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Model transformation with ATL

Ecore

Sourcemetamodel

ATL Targetmetamodel

Target

ModelSourcemodel

conforms to conforms toconforms to

conforms to

conforms to

conforms to

is transformed into

Sourcemodel2targetmodel.atl

Transformation using Atlas Transformation Language

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Example 1: UML to Relational DatabaseManagement Systems (RDBMS)

Example #3: Metamodel for BDI agents.

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UML Metamodel

PIM

PIM

Symbols

Metamodel

Concept

Relationship

Correspondence

UML to RDBMS

RDBMS Metamodel

We will now look into the agent metamodel.

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Parts of UML metamodel

Let us go through an example where we want to transform a UML model

to a Relational database management system

. The figure shows parts of the UML metamodel that you should alreadybe familiar with.

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Simple RDBMS metamodel

This figure shows a simple metamodel for RDBMS. It defines the most

important constructs for relational databases such as table, column, key

and foreign key.

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UML to RDBMS

Ecore

UMLmetamodel

ATL

UML to RDBMS

RDBMSmetamodel

RDBMS

ModelUML

model

conforms to conforms toconforms to

conforms to

conforms to

conforms to

is transformed into

Transformation using Atlas Transformation Language

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ClassModel2DBModel

ClassModel DBModel

- name : String - name : String

- elements: Classifier - tables : Table

- types : Type

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Class2Table

Class Table


- attributes: Attribute - columns : Column

- key : Column

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DataType2Type

DataType Type


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Attribute2Column

Attribute Column


- owner : Class

- type : DataType

- keyOf : Table

- type : Type- multivalued = Boolean

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Input Model

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Example 2: PIM4SOA to JackMM

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PIM4SOA Metamodel

PIM

PSM

Symbols

Metamodel

Concept

Relationship

Correspondence

PIM4SOA to JACK

Jack Metamodel

We will now look into the agent metamodel.

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Bottom Line

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MDD: beyond the buzzword

Modern model engineering techniques are ready for prime time in

software engineering They are based on:

four level architecture (CIM, PIM, PSM, Code)

meta-metamodel (e.g. MOF, Ecore),

with transfer and exchange mechanisms

with transformation mechanisms

growing collection of specialized metamodels

Object metamodels (Java, etc.)

Legacy metamodels (Relational, CWM)

Enterprise metamodels: Business, Healthcare,Transportation

Product and process metamodels

Automatic and semi-automatic generations, from high abstraction to

specific platforms

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Issue: Keeping Perspective

Modeling does not guarantee good applications

To model something, you must understand it

A bad model can still produce a bad application

MDA is not suited for every type of application

MDA does not compensate for lack of

good people

a good process

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Issue: Changing Developers Paradigm

Developers traditionally view development in code-centricterms Code production = progress

Code-centric design

Model-Centric Development Models are focal point of solutions

Code is a byproduct of development

Solve design problems at highest possible level

Model-Centric Design

Design centers on model Model is source code

Changes are made at highest possible level

Validate the code transformations

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Conclusion

MDA is probably not the silver bullet for softwareengineering,

But:

There is no reasonable alternative to MDD

Way to deal with new emerging technologies like Webservices in a smooth way

Decoupling the business part and the technical part ofinformation systems is a long term trend

MDA_0507Notes

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