- AspectT - Um Framework Orientado a Aspectos para SMAs Alessandro Garcia Uirá Kulesza {afgarcia, uira}@inf.puc-rio.br 16 Novembro, 2004

- AspectT -Um Framework Orientado a Aspectos

para SMAs

Alessandro GarciaUirá Kulesza

{afgarcia, uira}@inf.puc-rio.br

16 Novembro, 2004

Laboratório de Engenharia de Software – PUC-Rio 2

Revisão

• Frameworks Conceituais• Linguagens de Modelagem• Metodologias

• Frameworks e Plataformas– MAS Framework, RETSINA, ...– JADE e JADEX– AspectT


Roteiro• Motivação• O Framework Orientado a Aspectos

• Propriedades de Agência• Limitações de Soluções Relacionadas• Desenvolvimento Orientado a Aspectos

• O Framework Orientado a Aspectos para SMAs– A Arquitetura – Os Pontos de Flexibilidade– O Método de Desenvolvimento

• Um Estudo de Caso

• Estudos Empíricos• Conclusões


From Objects to Agents…

• An agent architecture includes:– basic functionality or services– interaction, adaptation, autonomy, learning, roles…

• Incorporation of agent properties into the system is a major source of complexity

• Separation of agent-specific concerns is crucial– reusability and maintainability


Collaboration

Mobility Learning

Roles

The Problem

• The agent properties are not orthogonal– crosscut each other and the agent’s basic functionality

Interaction

Adaptation Autonomy

Basic Functionality

architectural component

Some properties: - required as the system evolves - dynamic replacement


The Problem

• Multiple agent types heterogeneous architectures

Collaboration

Mobility Learning

Roles

Interaction

Adaptation Autonomy

Basic Functionality

Reactive Information Agents

Interaction

Adaptation Autonomy

Learning

Roles

Cognitive User Agents

Basic Functionality


The Problem

• Multiple agent types heterogeneous architectures

Collaboration

Mobility Learning

Roles

Interaction

Adaptation Autonomy

Agenthood

AdditionalProperties

Basic Functionality

Reactive Information Agents

Interaction

Adaptation Autonomy

Agenthood

AdditionalProperties

Mobility Learning

Roles

Cognitive User Agents

Basic FunctionalityNeed for a more flexiblearchitectural approach


Col

labo

ratio

n

The Problem: Detailed Design ViewAgent

goals...

addGoal()executePlan()…

InterfaceAgent

receiveInstruction()monitor()...

InformationAgent

search(Keyword)search(Keywords)…

UserAgent

getUser()checkPreference()…

Role

agentsprotocol

Caller

sendRequest()receiveResponse()...

Answerer

receiveRequest()sendResponse()...

Plangoal

preCond()posCond()…

action1()action2()...

Plan1action1()action2()action3()...

Plan2

Basic Functionality

getName()addAgent()…

caller answerer

DB userNameuser

efectorsadaptersthreads

adapters

move()returnHome()

itinerary

processInformation()

LCs

processInformation()

LCs

move()returnHome()startRole()

itineraryremoteEnvironmentsroles

processInf ()startRole()

LCsroles

processInf ()

LCs

sendMsg()receiveMsg()addAdapter()removeAdapter()notifyAdapters()makeDecision()startThread()

roles

startRole()

addAdapter()removeAdapter()notifyAdapters()

Mobility

Collaboration Adaptation

Autonomy

Interaction Learning

public Result searchKW(String KW) { adaptKnowledge(KW); processInformation(KW); ... ... << searching-specific code >> ... ... if (result = null) { this.move(KW) }}


The Problem: Detailed Design View

LMSprocessInformation()getLR()…

LearningComponent

learningRateprocessInformation()…

TD-LearningprocessInformation()getTD()getReward()setReward()…

Agentgoalsplans...

addGoal()executePlan()…

InterfaceAgentreceiveInstruction()monitor()...

InformationAgentsearch(Keyword)search(Keywords)…

UserAgentgetUser()checkPreference()…

Role

agentsprotocolgetName()addAgent()removeAgent()…

Caller

sendRequest()receiveResponse()...

AnswererreceiveRequest()sendResponse()...

Learning Crosscutting concerns Code replication Functional encapsulation is lost Difficult to transform objects into agents …

Drawbacks

MASs difficult to understand, maintain and reuseMASs difficult to understand, maintain and reuse


Solution

• AspectT: An Aspect-Oriented Framework– Modularization of crosscutting agent concerns– Flexible composition of agent properties– (Un)pluggability of agent properties– From objects to agents: transparent evolution– Avoidance of code replication– Improvements on reusability and maintainability


Agent Properties

– Agenthood Concerns [OMG00]:• Knowledge, Interaction, Autonomy, and Adaptation

– Additional Concerns: • Mobility, Learning, and Collaboration

OBJECT MANAGEMENT GROUP – AGENT PLATFORM SPECIAL INTEREST GROUP. Agent Technology – Green Paper. Version 1.0, September 2000.


Concerns in Multi-Agent Systems

• Agenthood Concerns

Knowledge

Legend:

mandatory feature

optional feature

alternative feature or feature

IntrinsicKnowledge

KnowledgeType

ProceduralRepresentation

KnowledgeRepresentation

… SemanticNets

Knowledge

KnowledgeStructuring Model

ExtrinsicKnowledge

Belief

Goal

Plan

Action

Pre-Conditions Post-Conditions

IntrinsicKnowledge

KnowledgeType

ProceduralRepresentation

KnowledgeRepresentation

… SemanticNets

Knowledge

KnowledgeStructuring Model

ExtrinsicKnowledge

Belief

Goal

Plan

Action

Pre-Conditions Post-Conditions




Interaction Adaptation

SensoryBehavior

MessageSending

InteractionBehavior

Interaction

EffectorSensor

MessageReception Knowledg

eAdaptatio

n

BehaviorAdaptatio

n

Adaptation

Adaptation

Protocol

Kind ofAdaptatio

nAdapter

Legend:

mandatory feature

optional feature


1..* 1..*1..*




Autonomy

Legend:

mandatory feature

optional feature


ExecutionAutonomy Decision

Autonomy

Autonomy

ProactiveAutonomy

ThreadStrategy



• Additional Concerns Collaboration Learning

Learning

LearningProtocol

LearningTechnique

Legend:

mandatory feature

optional feature


TD-Learning … LMS

Role

ExtrinsicKnowledge

Role Type

Collaboration

Protocol

Collaboration

AgentProperty

*

1..*1..* 1..*



• Additional Concerns Mobility

Legend:

mandatory feature

optional feature


MobilityStrategy

WeakMobility

StrongMobility

Mobility

MobilityForm


Related Work

• The need for separation of agent concerns is widely recognized

• JAFIMA Framework [Kendall99]– Layered architectures

• Brainstorm Framework [Ama98]– Reflective architectures [Briot99, Ama98]

• SkeletonAgent Framework [Camacho03]– Mediator-based architectures


Related Work – Agent Architectures

ADAPTATION

KNOWLEDGE

SENSORY

AUTONOMY

COLLABORATION

TRANSLATIONTRANSLATION

MOBILITY

KENDALL, E. et al. A Framework for Agent Systems. Implementing Application Frameworks – Object-Oriented Frameworks at Work, M. Fayad et al. (eds.). John Wiley & Sons: 1999.

• JAFIMA Framework– Layered Agent Architecture [Kendall99]


Col

labo

ratio

n

Knowledge

Layered Agent Architectures

Agent Beliefs

nameaddAdapter()removeAdapter()notifyAdapters()

PrimitiveBeliefs

…

CompositeBeliefs

update()

ObservableaddAdapter()removeAdapter()notifyAdapters()

Adapter

adapt()

Observer

goalsplansadaptersaddAdapter()removeAdapter()notifyAdapters()addAgent()removeAgent()executePlan()...

RolecollaboratingAgentscollaborationProtocoladaptersaddAdapter()removeAdapter()notifyAdapters()addAgent()…

ChairpaperssubmissionDeadlinereviewDeadlineaddAgent()removeAgent()…

Reviewer

MyPapernew()coauthorskeywordspublisherstatus

chairtoReviewPapersreviewDeadlinefillForm()updateForm()getChairName()…

Legend:Adaptation Concern

public void fillForm(...) { ... notifyAdapters(); ...}

Adaptation


Reflective Agent Architecture

MOP

Base Level

Meta-Level

object(intrinsic

knowledge)

interactionmeta-object

adaptationmeta-object

autonomymeta-object

Agent A

object(intrinsic

knowledge)

interactionmeta-object

adaptationmeta-object

autonomymeta-object

Agent Blearning

meta-objectmobility

meta-object

messageinterception

messageinterception


• E.g.: Brainstorm, Meta-DIMA, …


Mediator-Based Architectures

• Mediator-Based Agent Architectures [Cam03]

Mediator

Interaction Adaptation

MobilityLearning Bidirectional coupling


Mediator-Based Architectures


Related Work – Detailed Design

• Use of OO design patterns– Interaction: Adapter Pattern [Kendall99]– Adaptation: Observer Pattern [Kendall99]– Roles: Role Object Pattern [Baumer97]– Learning: Observer Pattern with Strategy Pattern [SML04]– Mobility: Itinerary Pattern [UT01]

• The design patterns are not able to modularize crosscutting agent concerns


Col

labo

ratio

n

Basic Functionality

Related Work – Detailed Design

• Adaptation: Observer Pattern [Kendall99]

Agent Beliefs


PrimitiveBeliefs

…

CompositeBeliefs

update()


Adapter

adapt()

Observer




Reviewer

MyPaper

new()coauthorskeywordspublisherstatus





Crosscutting Concerns in MASs

• 6 Classical Crosscutting Concerns– Interaction, Adaptation and Autonomy– Collaboration, Learning and Mobility


Interaction

• Motivation Example

PersonalAgenda

timeSlots…addAppointment()addMeeting()notifyAgent()…

PersistentCurriculum

addResearchKW()addPublication()addAward()addConference()updateAddress()…

InitialInterface

barCollor…getUserAnswer()getAnswerTime()…

Agentbelief1belief2...


action1()action2()action3()action4()...

Plan1action1()action2()action3()action4()...

Plan2

…action1()action2()action3()action4()...

Chairaction1()action2()action3()action4()...

Reviewer

Kernel Collaboration

Environment

Effector SensorsenseEvent()receiveMsg()...

send()...

Legend:Interaction Concern

effectorssensorsinboxoutbox...

receiveMsg()sendMsg()senseEvent()



Environment

Interaction• Motivation Example

PersonalAgenda




InitialInterface


Agentbelief1belief2sensorsinboxoutbox...

action1()action2()receiveMsg()sendMsg()senseEvent()...



Plan2



Reviewer




public void actionN(...) { ... agent.sendMsg(); ...}

public void addPublication(...) { ... sensor.senseEvent(); ...}


send()...


Interaction


Environment

PersonalAgenda




InitialInterface


Agentbelief1belief2sensorsinboxoutbox...

action1()action2()receiveMsg()sendMsg()senseEvent()...



Plan2



Reviewer




public void actionN(...) { ... agent.sendMsg(); ...}

public void addPublication(...) { ... sensor.senseEvent(); ...}

• Problem: How to separate the interaction concern from the other agency concerns?


send()...


Adaptation

• Motivation Example

Col

labo

ratio

n

Kernel

Agent Beliefs


PrimitiveBeliefs

…

CompositeBeliefs

update()


Adapter

adapt()

Observer




Reviewer

MyPaper

new()coauthorskeywordspublisherstatus




• Problem: How to separate the adaptation concern from the other agency concerns?


Collaboration

• RolesThe Role Object Pattern withThe Decorator Pattern [KO96]

UserAgent

CollaborativeUserAgent

addRole()getRole()hasRole()getInterests()getAgenda()getResearchStage()…

userNamemyRolesresearchInterestsresearchersinformationAgentsgetInterests()getStage()getAgenda()…

UserAgentRole

userAgentCoregoalsplanscollaboratingAgentscollaborationProtocolgetInterests()getResearchStage()getAgenda()

CallerpaperssubmissionDatereviewDeadline…

Reviewer

papersToReviewchairNamereviewDatebiddingDate…

Agent

getName()setGoal()setPlan()…

roles

agent core

ChairpaperssubmissionDatereviewDeadline…

AdditionalReviewer

reviewer…

Legend: ____ replicated code

Decorator classes

Collaboration concern

intrinsic role

extrinsic roles

interface toall roles

PlanexecutePlan()


Collaboration

UserAgent

CollaborativeUserAgent

addRole()getRole()hasRole()getInterests()getAgenda()getResearchStage()…

userNamemyRolesresearchInterestsresearchersinformationAgentsgetInterests()getStage()getAgenda()…

UserAgentRole

userAgentCoregoalsplanscollaboratingAgentscollaborationProtocolgetInterests()getResearchStage()getAgenda()

CallerpaperssubmissionDatereviewDeadline…

Reviewer

papersToReviewchairNamereviewDatebiddingDate…

Agent

getName()setGoal()setPlan()…

roles

agent core

ChairpaperssubmissionDatereviewDeadline…

AdditionalReviewer

reviewer…

intrinsic role

extrinsic roles

interface toall roles

PlanexecutePlan()

• Problem: How to separate the roles from the agent’sbasic functionality?

• Avoid code replication

Legend: ____ replicated code

Decorator classes

Collaboration concern


Learning• The Observer Pattern with the

Strategy Pattern [SML04]

Agent RevisionProposalpaperoaoerInterestevaluationisAccepted()getReviewer()getPaperInterest()getEvaluation()…

ObservableaddLC()removeLC()notifyLC()

LMSprocessInf()getLR()…

LearningComponent

goalsplansagentsaddAgent()…

RoleagentsprotocolgetName()addAgent()removeAgent()…

ChairpapersLClistsubmissionDatereviewDeadlineaddLC()removeLC()notifyLC()getPapers()getReviewers()...

ReviewerchairNameLClistsetChair()addLC()removeLC()notifyLC()setChair()

UserAgentgoalsplansAgentsmyRolesLClistaddAgent()removeAgent()executePlan()addLC()removeLC()notifyLC()…

PlangoalagentpreConditions()posConditions()createObject()executePlan()…

DistributionPlan

LClistaddLC()removeLC()notifyLC()executePlan()distribute()...

JudgementPlan

JudgementReceptionPlan

learningRateprocessInf()…

TD-LearningprocessInf()getTD()getReward()…

LClistaddLC()removeLC()notifyLC()executePlan()judgeProposal()...

LClistaddLC()removeLC()notifyLC()executePlan()evaluate ()...

Kernel

Col

labo

ratio

n

Learning Concern


Agent RevisionProposalpaperoaoerInterestevaluationisAccepted()getReviewer()getPaperInterest()getEvaluation()…

ObservableaddLC()removeLC()notifyLC()

LMSprocessInf()getLR()…

LearningComponent

goalsplansagentsaddAgent()…

RoleagentsprotocolgetName()addAgent()removeAgent()…

ChairpapersLClistsubmissionDatereviewDeadlineaddLC()removeLC()notifyLC()getPapers()getReviewers()...

ReviewerchairNameLClistsetChair()addLC()removeLC()notifyLC()setChair()

UserAgentgoalsplansAgentsmyRolesLClistaddAgent()removeAgent()executePlan()addLC()removeLC()notifyLC()…

PlangoalagentpreConditions()posConditions()createObject()executePlan()…

DistributionPlan

LClistaddLC()removeLC()notifyLC()executePlan()distribute()...

JudgementPlan

JudgementReceptionPlan

learningRateprocessInf()…

TD-LearningprocessInf()getTD()getReward()…

LClistaddLC()removeLC()notifyLC()executePlan()judgeProposal()...

LClistaddLC()removeLC()notifyLC()executePlan()evaluate ()...

Kernel

Col

labo

ratio

n

• Problem: How to separate the learning concern from the other agency concerns?

Learning


Mobility

Agent

Serializable

JADEAgent

Role

collaboratingAgentscollaborationProtocolgetName()addAgent()removeAgent()…

Chair Reviewer UserAgent

researchInterestspublicationsreviewsitineraryaddPCparticipation()move()beforeMove()afterMove()setKeyword()addHost()…

Plan

goalagent…clone()execute ()…

CVUpdatePlan DistributionPlan InformationGatheringPlan

getName()move()beforeMove()afterMove()..

learningComponentsaddLC()...execute ()sendQuery()...

– mobility-specific members– methods with some mobility code

Col

labo

ratio

n

Mobility

BasicConcerns

Interaction

... ...

Effector Sensorreceive()senseEvent()...

send()...

– realization of the serialization interface– mobility-specific classes

goalsplanssensorseffectorsaddAgent()sendMsg()receiveMsg()…

Legend:

chairNamepapersToReviewlearningComponentssetChair()addLC()removeLC()notifyLC()returnJudgement()…

profilesaddLC()removeLC()notifyLC()execute ()distributePapers()getProfile()...

public class Sensor implementsSerializable {

...}

ItinerarygetName()move()beforeMove()afterMove()..

11

2

2

5

6

4

public Result sendQuery(...) { ...if (queryResult.value != null) {

...agent.returnHome(); }

...}

papersitinerarysubmissionDeadlinereviewDeadlinemove()beforeMove()afterMove()distributeProposal()addHost()... 3 3

4

learningComponentsaddLC()removeLC()execute ()updateCV()...public void execute(...) {

...if (date.getDay() == 1) {

...agent.move(); }

...}

Agent

Serializable

JADEAgent

Role

collaboratingAgentscollaborationProtocolgetName()addAgent()removeAgent()…

Chair Reviewer UserAgent

researchInterestspublicationsreviewsitineraryaddPCparticipation()move()beforeMove()afterMove()setKeyword()addHost()…

Plan

goalagent…clone()execute ()…

CVUpdatePlan DistributionPlan InformationGatheringPlan

getName()move()beforeMove()afterMove()..

learningComponentsaddLC()...execute ()sendQuery()...

– mobility-specific members– methods with some mobility code

Col

labo

ratio

n

Mobility

BasicConcerns

Interaction

... ...

Effector Sensorreceive()senseEvent()...

send()...

– realization of the serialization interface– mobility-specific classes

goalsplanssensorseffectorsaddAgent()sendMsg()receiveMsg()…

Legend:

chairNamepapersToReviewlearningComponentssetChair()addLC()removeLC()notifyLC()returnJudgement()…

profilesaddLC()removeLC()notifyLC()execute ()distributePapers()getProfile()...

public class Sensor implementsSerializable {

...}

ItinerarygetName()move()beforeMove()afterMove()..

1111

22

22

55

66

44

public Result sendQuery(...) { ...if (queryResult.value != null) {

...agent.returnHome(); }

...}

papersitinerarysubmissionDeadlinereviewDeadlinemove()beforeMove()afterMove()distributeProposal()addHost()... 33 33

44

learningComponentsaddLC()removeLC()execute ()updateCV()...public void execute(...) {

...if (date.getDay() == 1) {

...agent.move(); }

...}


AspectT

• Supports the OO programming of:– Agents, goals, plans, actions, and beliefs

• Supports the AO modularization and programming of:– Interaction, Adaptation, and Autonomy– Collaboration, Learning, and Mobility


Aspects

• AspectJ: general-purpose aspect-oriented language

“Crosscutting Concerns”

OO Solution

Classes

Aspect-Oriented SolutionAspect

JoinPoints


Aspects: An Example

ServerDBreferencedisabledfailuresinitySistem()connectDB()disconnectDB()getReference()updateComplaint()getComplaints()registerHealthUnit()getHealthUnit()…

reportFault()fixServer()…

Client * 1

public Hashtable getComplaints(...) { try { ... << normal code >> ... } catch (FaultException e){ ... << exceptional code>> this.disabled = true; reportFault(); ... }}

public methods

methods implementingerror-handling-specific

behavior


failures

reportFault()fixServer()...

Aspects: An Example

ServerDBreferenceinitySistem()connectDB()disconnectDB()getReference()updateComplaint()getComplaints()registerHealthUnit()getHealthUnit()…

Client * 1

public methods

FaultHandler


Aspects: An Example

_services()services_()

IErrorDetection

failures

FaultHandler


disabled

Server

DBreference...

initSystem()connectDB()disconnectDB()getReference()...

crosscutting relationship

internal attribute

internal methods

inter-typedeclaration

advices

Legend: _beforeAdvice afterAdvice_ _aroundAdvice_

crosscuttinginterface

pointcutname

CHAVEZ, C. A Model-Driven Approach to Aspect-Oriented Design. PhD Thesis, Computer Science Department, PUC-Rio, April 2004, Rio de Janeiro, Brazil.


High-Level View of an Aspect

IServices

Server

_services()services_()

IErrorDetection

failures

FaultHandler


disabled

Server

DBreference...

initSystem()connectDB()disconnectDB()getReference()...


FaultHandler



Aspects: An Example

aspect FaultHandler { private boolean Server.disabled = false; private void reportFault() { System.out.println("Failure! Please fix it."); } public static void fixServer(Server s) { s.disabled = false; }

pointcut services(Server s): target(s) && call(public * *(..));

before(Server s): services(s) { if (s.disabled) throw new DisabledException(); }

after(Server s) throwing (FaultException e): services(s) { s.disabled = true; reportFault(); }}


Research on Aspects

• Aspect-oriented solutions are limited to general concerns:– Distribution– Persistence– Error handling– Logging– …


AspectT

• Supports the OO programming of:– Agents, goals, plans, actions, and beliefs

• Supports the AO modularization and programming of:– Interaction, Adaptation, and Autonomy– Collaboration, Learning, and Mobility

• Supports the integration with other MAS platforms:– JADE– TSpaces

• The Framework Structure • A High-Level View


AspectT

AspectT

AspectInt(interaction)

Kernel

AspectAd(adaptation)

AspectAut(autonomy)

AspectCo(collaboration)

AspectL (learning)

AspectM (mobility)Cidiane, Alessandro, Cláudio e Uirá

Alessandro, Sardinha, Uirá e Ruy

Total

Other Contributions: Eduardo, Cidiane, Karla, ...


IKnowledge IServices

High-Level View

Kernel

Legend:aspectual componentcomponentcrosscutting interfacenormal interface

BehaviorAdaptation

KnowledgeAdaptation

TravelingMessageReception

Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

RoleBinding

CollaborationProtocol

Collaboration

Mobility

MessageSending

ExtrinsicKnowledge

InformationGathering

LearningKnowledge

Learning


• Dynamic View– Agent Initialization

Learning

Mobility

Collaboration

AdaptationKernel

Autonomy

Interactionagentcreation goal and plan

initializations

optionalmandatory

initial point

1

sensor and effectorinitializations

beliefsinitialization

3

4

5

roleinitialization

6

beliefsinitialization

7

High-Level View

executionautonomy

2


• Dynamic View– Message Handling

Learning

Mobility

Collaboration

Autonomy

Adaptation

Interaction

incomingmessage

decision making

optionalmandatory

initial point

1

2

decisionplans

5 goal finding 6

belief adaptation

belief changes3

4

EnvironmentHigh-Level View

Kernel

7reactive

goal


• Dynamic View– Goal Achievement

Learning

Mobility

Collaboration

Autonomy

Adaptation

Interaction

behavior adaptation

optionalmandatory

initial point

9

reactivegoal7 goal creation 6

execution autonomy

8

role activation 11reactive

plan10

High-Level View

Kernel


• Dynamic View– Proactive Behavior

Learning

Mobility

Collaboration

Autonomy

Adaptation

Interaction

goal creation

ANDOR

optionalmandatory

proactivebehavior

initial point

23

learnedknowledge

changedknowledge

1

behavior adaptation

6

proactive goal4

execution autonomy

5

proactive plan7

High-Level View

Kernel


• Dynamic View– Role Binding/Activation

Learning

Mobility

Collaboration

Autonomy

Adaptation

Interaction

ANDOR

optionalmandatory

initial pointnew environment

initializationchanged

knowledge

1

1received message

2role binding

High-Level View

Kernel

1



Kernel

Kernel


BehaviorAdaptation

KnowledgeAdaptation


Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

RoleBinding


Collaboration

Mobility

MessageSending

ExtrinsicKnowledge


LearningKnowledge

Learning


Kernel

• Step 1: Define the Agent Kernel

BeliefGoal

Plan

Kernel

Agentnamegoalsplans…new()addBelief()setGoal()executePlan()...


Kernel

Agent

belief1belief2...goalsplanstoAchieveGoalstoPerformPlans

addGoal()removeGoal()setGoal()action1()action2()...

Belief

name...

PlanpreConditions()posConditions()execute()stop()

Goal

namesubgoals...

*

• Solution:


Interaction


Kernel

MessageReception

InteractionMessageSending

ServicesSensory

Environment


EnvClass3

EnvClass2

EnvClass1

environmentclasses

Agent

Plan

messagesenders

Aspect

InteractionAspectInt

• Solution:Sensory

sendMsg()

outgoingMsg_()

MessageSending Interaction

inboxoutbox

init()marshall()unmarshall()

Effector Sensor

sense()send()

sensing_()

MessageReception

receiveMsg()

incomingMsg_()

update() 1

3

2

4



High-Level View

Kernel


MessageReception

InteractionMessageSending

Traveling

RoleBinding


Collaboration

Mobility

ExtrinsicKnowledge


LearningKnowledge

LearningBehavior

Adaptation

KnowledgeAdaptation

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy



Agenthood Properties

Kernel


BehaviorAdaptation

KnowledgeAdaptation

MessageReception

Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

MessageSending

Traveling

RoleBinding


Collaboration

Mobility

ExtrinsicKnowledge


LearningKnowledge

Learning


AdaptationAspectAd

• Solution:

BehaviorAdapation

adapters

adaptBelief()findPlan()adaptSpecificBelief()findSpecificPlan()

Agent

Belief

knowledgeelementsobserved

Interaction

newGoal_()failedPlan_()planFinal_()

changedBelief_()newMsg_()

KnowledgeAdaptation Adaptation

executePlan()Plan

Agent

setGoal()

Adapter

adapt()

receiveMsg() 13

2

4

1

2

3

4


AutonomyAspectAut

• Solution:

4executePlan()

DecisionPlan

decisionGoalsproactiveGoalsautonomyDegree

initGenericGoals()initSpecificGoals()makeDecision()makeSpecificDecision()instantiateGoal()initThread()

Agent

Belief

observedelements

Interaction

events_()

GoalCreation

Autonomy

ProactivePlan

executePlan()

*

*newAgent_()

ExecutionAutonomy

receiveMsg()

3

1

2

4



• Step 2: Agenthood Properties

BeliefGoal

Plan

Kernel

Agentnamegoalsplans

new()addBelief()setGoal()executePlan()...

Interaction

GoalCreation

Autonomy

ExecutionAutonomy

BehaviorAdapation

KnowledgeAdaptation

Adaptation

MessageSending

MessageReception


Agent Types

• Step 3: Define Agent Types

KernelKernelKernelInterfaceAgent

receiveInstruction()monitor()memorize()...

InformationAgentsearch(Keyword)search(Keywords)search(Sentences)…


Agentnamebeliefsgoalsplans...

addBelief()addGoal()executePlan()…




Kernel


BehaviorAdaptation

KnowledgeAdaptation

MessageReception

Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

MessageSending

Traveling

RoleBinding


Collaboration

Mobility

ExtrinsicKnowledge


LearningKnowledge

Learning



Collaboration

Kernel


BehaviorAdaptation

KnowledgeAdaptation

MessageReception

Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

MessageSending

Traveling

Mobility


LearningKnowledge

Learning

RoleBinding

Collaboration


CollaborationAspectCo

RoleRole

PlanPlan

events_()

RoleBinding

Role3Role2

AgentType

belief1belief2...goalsplans

action1()action2()


Role1

action1action2...

Belief

beliefs

PlannamepreConditions()posConditions()

Goal

name

*

• Solution:



Collaboration

Kernel


BehaviorAdaptation

KnowledgeAdaptation

MessageReception

Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

MessageSending

Traveling

Mobility


LearningKnowledge

Learning

RoleBinding

Collaboration



Mobility

Kernel


BehaviorAdaptation

KnowledgeAdaptation

MessageReception

Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

MessageSending


LearningKnowledge

Learning

RoleBinding

Collaboration

Traveling

Mobility


MobilityAspectM

• Solution:

moving_()returning_()

Traveling

itinerary...

Mobility

init()move()addHost()prepareToMove()...

Role

AgentType



executePlan()...

*

is Mobile

move()returnHome()...

MobilityFramework

<<crosscutting interface>>

SpecificMobility

init()move()...

Plan

Legend: _beforeAdvice afterAdvice_ _aroundAdvice_



Mobility

Kernel


BehaviorAdaptation

KnowledgeAdaptation

MessageReception

Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

MessageSending


LearningKnowledge

Learning

RoleBinding


Collaboration

ExtrinsicKnowledge

Traveling

Mobility



Learning

Kernel


BehaviorAdaptation

KnowledgeAdaptation

MessageReception

Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

MessageSending

RoleBinding


Collaboration

ExtrinsicKnowledge

Traveling

Mobility


LearningKnowledge

Learning


LearningAspectL

• Solution:

learnPreferences()updatePreferences()...

Agent

Belief

Plan

events_()

InformationGathering Learning

LearningComponent

learningRateprocessInformation()...

belief1belief2...


LearningKnowledgeAspect

*


Additional Properties

• Step 4: Define the Additional Properties

KernelKernelKernel


Learning

InterfaceAgentreceiveInstruction()monitor()memorize()...

InformationAgentsearch(Keyword)search(Keywords)search(Sentences)…



Collaboration


Flexible Composition• Portalware

KnowledgeUpdating

BehaviorAdaptation

Kernel

Services

KnowledgeAdaptation


Interaction

Adaptation

GoalCreation

ExecutionAutonomyAutonomy

RoleBinding


Collaboration

Mobility


MessageSending

ExtrinsicKnowledge

- no learning component- no sensing behavior


Flexible Composition

KnowledgeUpdating

BehaviorAdaptation

Kernel

Services

KnowledgeAdaptation


Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

RoleBinding


Collaboration

MobilityMessageSending

Agenthood Additional Properties

Environment

ExtrinsicKnowledge

Sensory


LearningKnowledge

Learning

KnowledgeUpdating

BehaviorAdaptation

Kernel

Services

KnowledgeAdaptation


Interaction

Adaptation

GoalCreation

ExecutionAutonomy

Autonomy

RoleBinding


Collaboration

MobilityMessageSending


Environment

ExtrinsicKnowledge

Sensory


LearningKnowledge

Learning

• Expert Committee - learning component- sensing behavior


Um Estudo de Caso

• Descrever o uso do framework em um exemplo de SMA

• Aplicar em alguns cenários do EC as diretrizes de projeto detalhado

• Projeto incremental de cada um dos componentes que definem a arquitetura usando o framework como base


Cenários - ExpertCommittee• Cenário 1: Atribuição básica de artigos• Cenário 2: Avaliação da proposta de revisão


Diretrizes de projeto detalhado

• Passo 1: Refinar componente Kernel• Passo 2: Refinar componente Interaction• Passo 3: Refinar componente Adaptation• Passo 4: Refinar componente Autonomy• Passo 5: Refinar componente Mobility• Passo 6: Refinar componente Learning• Passo 7: Refinar componente Collaboration


Passo 1: Refinar o kernel do agente

• Definir os tipos de agentes, bem como suas crenças, metas e planos

BeliefGoal

Plan

Kernel

Agentnamegoalsplans…new()addBelief()setGoal()executePlan()...


Passo 1: Refinar o kernel do agenteAgent

InformationAgent ResearcherUserAgentuserNameresearcherListresearchInterestresearcherStageagenda...

set...()get...()

...sendCNPqReport()...

...

...

namereactiveGoalListreactivePlanListtoAchieveGoalstoPerformPlansagentList

Agent Types


Passos 1 e 7: Refinar o kernel do role

...

...

Chair

goalListplanListpaperListreviewerListproposalEvalDeadlinereviewDeadlinepapersWithoutReviewers

sendReviewProposal()receiveProposalResponse()receiveRetirementRequest()...

Reviewer

chairNameplanListacceptedPapersrejectedPapers

receiveProposal()judgesProposal ()askReviewerRetirement()sendProposalResponse()...

Plan

PaperDistribution

ReviewerInvitation

ProposalRespEvaluationFinalDistribution

execute()precondiitions()...

execute()precondiitions()...execute()precondiitions()...

AuctionInitialization

ProposalReception

AuctionBidding

ProposalJudgementexecute()precondiitions()...

ResearcherUserAgentuserNameresearcherListresearchInterestresearcherStageagenda...

set...()get...()

...sendCNPqReport()...

<<crosscuts>>

<<crosscuts>>

Agent Roles and Agent Plans


Passo 2: Refinar a Interação do agente • Definir sensores e efetuadores• Definir parsers concretos• Definir aspectos concretos de Interação

– Inicializar sensores e efetuadores• Definir pontos de envio e recepçaõ de msgs

Adaptation

Kernel

IMessageReception

InteractionIMessageSending

IServicesISensory

Environment


Passo 2: Refinar a Interação do agente

Autonomy

Adaptation

ISensory

sendMsg()

outgoingMsg_()

IMessageSending Interaction

inboxoutbox


Agent

Plan

Effector Sensor

sense()send()

Class3

Class2

Class1

environmentclasses

messagesenders

Aspect

sensing_()

IMessageReception

receiveMsg()

incomingMsg_()


Passo 2: Refinar a Interação do agente

Autonomy

ISensory

sendMsg()

outgoingMsg_()

IMessageSending Interaction

inboxoutbox


sensing_()

IMessageReception

receiveMsg()

incomingMsg_()

Effector Sensor

sense()send()

JADEEffector BBEffector JADESensor

send() send() sense() sense()

BBSensor

Parser

marshalMsg()unmarshalMsg()

JADEParser

sense()

Agent Sensors, Effectors and Parsers


Passos 2 e 7: Refinar a Interação do role

ResearcherUserAgent

ISensory

sendMsg()

outgoingMsg_()

IMessageSending

sensing_()

IMessageReception

Interaction

inboxoutbox

init()marshall()unmarshall()sendMsgEffector()

receiveMsg()

incomingMsg_()

ISensory

sendMsg()

outgoingMsg_()

IMessageSending

sensing_()PersistentCV

updateInterest()Agenda

updateAgenda()

ChairInteraction

init()sendMsgEffector()...

PaperDistributionPlan

DSInterfaceMobility

prepareToMove()prepareReturn()

GUIoperation()

Message SendingSensors and

Effectors InitializationExternal Sensory


Passo 3: Refinar a Adaptação do agente

• Definir adaptação de crenças a partir do recebimento de mensagens externas

• Definir adaptação de planos a partir de metas que precisam ser alcançadas

Adaptation

IKnowledgeUpdating

IPlanAdaptation

Kernel

IBeliefAdaptation

IMessageReception

Interaction

Adaptation

IMessageSending

IServices


Passo 3: Refinar a Adaptação do agente

Agent

removeAgent()...Belief

updateKeywords()...

executePlan()Plan

IPlanAdaptation

adapters


Interaction


AgentchangedBelief_()newMsg_()

IBeliefAdaptation Adaptation

setGoal()

receiveMsg()...


IPlanAdaptation


Passos 3 e 7: Refinar a Adaptação do role

Agent


updateKeywords()...

executePlan()Plan

IPlanAdaptation

adapters


Interaction




setGoal()

receiveMsg()...

...

adaptSpecificBelief()findSpecificPlan()updateDataPaperDist()...

changedBelief_()

IBeliefAdaptation Chair

Adaptation PaperDistributionPlan

updateKeywords()...

ProposalEvaluationPlan

...Chair

paperList...

BeliefAdaptation PlanAdaptation


IPlanAdaptation


Passos 3 e 7: Refinar a Adaptação do role

Agent


updateKeywords()...

executePlan()Plan

IPlanAdaptation

adapters


Interaction




setGoal()

receiveMsg()...

...

adaptSpecificBelief()findSpecificPlan()...

changedBelief_()

IBeliefAdaptation Reviewer

Adaptation ProposalReceptionPlan

updateKeywords()...

ProposalJudgementPlan

...Reviewer

papersToReview...


IServices

Passo 4: Refinar a Autonomia do agente

• Definir inicialização de metas do agente

• Definir estratégias de criação de metas– Reativas– Proativas– Decisão

Autonomy

IKnowledgeUpdating

IPlanAdaptation

Kernel

IMessageReception

Interaction

Adaptation

IGoalCreation

IExecutionAutonomy

Autonomy

IMessageSending

IBeliefAdaptation


Passo 4: Refinar a Autonomia do agente

executePlan()DecisionPlan


initGenericGoals()initSpecificGoals()makeDecision()makeSpecificDecision()instantiateGoal()initThread()

Agent

Belief

observedelements

Interaction

events_()

IGoalCreation

Autonomy

ProactivePlan

executePlan()

*

*newAgent_()

IExecutionAutonomy


Passos 4 e 7: Refinar a Autonomia do role


initGenericGoals()initSpecificGoals()makeDecision()makeSpecificDecision()Instantiate*Goal()initThread()

Autonomy

receiveMsg()...

executePlan()...

PaperDistributionGoal

specificGoals...

initSpecificGoals()makeSpecificDecision()

events_()

IGoalCreation

ChairAutonomy

ProposalReceptionGoal

executePlan()...

Chair

Agenda

addAppointment()...

Goal Instantiation


Passos 4 e 7: Refinar a Autonomia do role


initGenericGoals()initSpecificGoals()makeDecision()makeSpecificDecision()instantiate*Goal()initThread()

Autonomy

receiveMsg()...

executePlan()...

DistributePaperGoal

specificGoals

initSpecificGoals()makeSpecificDecision()instantiateReactiveGoal()instantiateProactiveGoal()instantiateDecisionGoal()

events_()

IGoalCreation

ProposalEvaluationGoal

executePlan()...

Reviewer

Agenda

addAppointment()...

ReviewerAutonomy


Passo 6: Refinar o Aprendizado do agente

• Padrão de Projeto que pode ser aplicado na definição de aprendizado para SMAs

• Definição de eventos de interesse e coleta de informações para o processo de aprendizado

• Definição de algoritmos de aprendizado a serem utilizados

• Atualização do conhecimento do agente

Autonomy




<< crosscutting interface >>

events_() initLC()learnPreferences()...


Agent

Role

Plan

events_()


LearningComponent


attribute1...method1()...

LearningKnowledge

*

SpecificLearning



Learning

operation1()...


Passo 6: Aprendizado no EC

• Agente-Reviewer atualiza os graus de interesse do usuário baseado na aceitação ou rejeição de artigos atribuídos para ele

• Agente-Chair atualiza preferências do usuário baseado no feedback de propostas enviadas para agentes reviewers.



paperInterestevaluation...getInterest()...

LearningKnowledgeRevisionProposal

reviewerpaperdeadlinesisAccepted()getReviewer()getPaper()…





Learning

initTDLearning()getResponse()...

ReviewerLearning TDLearning

processInformation()getTD()getReward()setReward()…

Reviewer

UserAgent

JudgementPlanexecute()judgeProposal()...

LearningComponent


*

events_()


Empirical Studies

• 4 qualitative studies and 1 quantitative study• 3 prototypes in different application domains• Portalware URL: www.teccomm.les.inf.puc-rio.br/alessandro/portal.zip• Expert Committee URL: www.teccomm.les.inf.puc-rio.br/alessandro/ec.zip

System Name Domain AgentTypes

Agency ConcernsLOC

In Ad Au Co Ro Mo Le

TSA TrafficSimulation Reactive 1859

Portalware v.1 (qualitative study) Development

Environment

Reactive 1654

Portalware v.2 (quantitative study)

Reactive Cognitive 3063

Expert Committee ConferenceManagement Hybrid 6564


Evolution of the Studies

Portalware(Quantitative)Case Study 5:

• The Experimental Setting– Subjects:

• 3 PhD Students and 1 Master’s Student

– Almost 2 years:• January 2001 – December 2002

– GQM methodology– Use and evaluation of the

assessment framework

• Two phases– Construction– Reuse and Maintenance

Traffic Simulator

Architecture

Portalware(Mapping)

Case Study 1:

Case Study 3:

ExpertCommitteeCase Study 4:

Portalware(Comparison)Case Study 2:

GARCIA, A. et al. Separation of Concerns in Multi-Agent Systems: An Empirical Study. In: Software Engineering for Multi-Agent Systems II, Springer, LNCS 2940, March 2004, pp. 49-72.


The Quality Model and Metrics

Reusability Understandability

FlexibilityMaintainability

Size

Coupling

Cohesion

Separation of Concerns

Factors Internal Attributes Qualities

VS

LOCNOAWOC

CBC

LCOO

CDC

CDO

CDLOC

Metrics

DIT

Reusability Understandability


Size

Coupling

Cohesion



VS

LOCNOAWOC

CBC

LCOO

CDC

CDO

CDLOC

Metrics

DIT

• Measure well-known software attributes


The Metrics

ReusabilityUnderstandability


Size

Coupling

Cohesion



VS

LOC

NOAWOC

CBC

LCOO

CDC

CDO

CDLOC

Metrics

DIT

Concern Difusion over ComponentConcern Difusion over OperationConcern Difusion over LOCVocabulary SizeLines of CodeNumber of AttributesWeighted Operations per Component

Coupling between ComponentesDepth of InheritanceLack of Cohesion in Operations

Chidamber, S., Kemerer, C. “A Metrics Suite for Object Oriented Design”. IEEE Transactions on Software Engineering, 20 (6), June 1994, pp. 476-493.


The Quantitative Study

CounterProposal

ailabilityPlan

Agent

CollaborativeAgent

CollaborationCore

Property

Autonomy AdaptationInteraction

Collaboration

CollaborationRole

Editor Caller User

AgentInformation

Agent

InterfaceAgent

MiddleAgent

Mediator Pattern

Role Pattern

Plan

Answerer

SearchingPlan

StrategyPattern

ContentSupplier

Knowledge

Proposal

Composite Pattern


Answerer

CounterProposal

ailabilityPlan

Agent

UserAgent

InformationAgent

InterfaceAgent

MiddleAgent

Plan

SearchingPlan

Knowledge

Proposal

Autonomy

Interaction

Collaboration

Adaptation

EditorContentSupplier

Caller

The Quantitative Study


Quantitative Evaluation (I)

Ponto de Vista do Sistema

0102030405060708090

100

Nro. Componentes

LOCNro. Atributos

Peso de Operações

Acoplamento Componentes

Profundidade Herança

Falta de Coesão

%

OOOA

7% 12% 9% 6% 9% 40% 3%

Vocabulary Size

System Viewpoint

Patterns

Aspects

Attributes

Weighted Operations

Coupling

Inheritance

Cohesion

GARCIA, A. et al. Separation of Concerns in Multi-Agent Systems: An Empirical Study. In: Software Engineering for Multi-Agent Systems II, Springer, LNCS 2940, March 2004, pp. 49-72.


Quantitative Evaluation (II)

CounterProposal

ailabilityPlan

Agent

CollaborativeAgent

CollaborationCore

Property

Autonomy AdaptationInteraction

Collaboration

CollaborationRole

Editor Caller User

AgentInformation

Agent

InterfaceAgent

MiddleAgent

Mediator Pattern

Role Pattern

Plan

Answerer

SearchingPlan

StrategyPattern

ContentSupplier

Knowledge

Proposal

Composite Pattern


Reuse and Maintenance Phase

• Evolution and Reuse ScenariosS1) Change on the Agent Roles (Evolution)S2) Creation of an Agent Type (Evolution)S3) Reuse of the Agenthood Concern (Reuse)S4) Inclusion of Collaboration in an Agent Type (Reuse and

Evolution)S5) Reuse of Roles (Reuse)…


Reuse and Maintenance Phase

MODIFIABILITYEXTENSIBILITY

ChangedEntities

ChangedOperations

AddedEntities

AddedOperations

ChangedRelations.

AddedRelations.

AddedLOCs

ChangedLOCs

CopiedEntities

CopiedLOCs

PO AO PO AO PO AO PO AO PO AO PO AO PO AO PO AO PO AO PO AOS1 1 1 3 3 5 5 2 3 0 0 15 15 101 98 1 1 - - - -S2 0 0 2 2 4 4 0 0 0 0 10 10 84 86 0 0 - - - -S3 0 0 2 2 4 4 0 0 0 0 10 10 84 86 0 0 0 0 0 0S4 0 0 2 3 8 8 0 0 0 0 29 25 188 167 0 8 0 0 0 0S5 1 1 2 1 0 0 1 1 0 0 4 2 16 14 0 0 0 0 6 6S6 0 0 0 0 0 0 0 0 0 0 0 0 15 15 0 0 - - - -S7 5 1 0 0 0 0 0 0 5 2 1 1 0 0 5 1 0 0 40 0

The aspect-oriented approach required less modification of the selected MAS


The Pattern Language

absent knowledge

Environment


Autonomy

Mobility

Legend: Crosscuts

new message

new message

incoming message

new goal

collaborationjoining

agent creation

Kernel

new eventabsent knowledge

new eventoutgoing

message

Roles

Interaction Learning

Adaptation


Conclusions

• AspectT enables– improved modularization of agent properties– flexible composition of agent properties– (un)pluggability of agent properties– from objects to agents: transparent evolution– avoidance of code replication– improvements on reusability and maintainability

• Empirical evidence– The proposed approach is promising to improve separation of

concerns in complex agent architectures


FAQ

• Why should I use the AspectT framework?– It supports the fundamental agent characteristics– It supports common abstractions in agent modeling

• Agents, Goals, Plans, Actions, Beliefs, Roles, ...– Easy integration with MAS platforms– Tested in three different applications– Comprehensive documentation

• When should we use the AspectT framework?– Not only in complex software agents– The aspects can be applied separately to some extent

• E.g.: Interaction, Roles, Learning, Mobility


FAQ

• What are the framework limitations?– It does not support some MAS abstractions (e.g.

organizations)

• Which MAS platform should we use together with the AspectT framework?– JADE (mobility, remote communication)– Blackboard (local communication)– TSpaces, JavaSpaces (local and remote communication)


Documentation

• AspectT

• The Method/ProcessGARCIA, A.; KULESZA, U.; LUCENA, C. Aspectizing Multi-Agent Systems: From

Architecture to Implementation. "Software Engineering for Multi-Agent Systems III”, Springer-Verlag, LNCS, December 2004.

GARCIA, A. et al. An Aspect-Based Approach for Developing Multi-Agent Object-Oriented Systems. Proceedings of the 15th Brazilian Symposium on Software Engineering, Rio de Janeiro, Brazil, October 2001, pp. 177-192. (Nomination for the Best Paper Award)

GARCIA, A.; LUCENA, C.; COWAN, D. Agents in Object-Oriented Software Engineering. Software: Practice and Experience, Elsevier, May 2004, pp. 1-32.

GARCIA, A.; KULESZA, U.; LUCENA, C. From Objects to Agents: An Aspect-Oriented Pattern Language. Submitted to ACM Transactions on Software Engineering Methodologies.


Documentation

• Empirical Studies

• AspectL

GARCIA, A. et al. Engineering Multi-Agent Systems with Aspects and Patterns. Journal of the Brazilian Computer Society, Special Issue on Software Engineering and Databases, N. 1, Vol. 8, July 2002, pp. 57-72.

GARCIA, A. et al. Separation of Concerns in Multi-Agent Systems: An Empirical Study. In: Software Engineering for Multi-Agent Systems II, Springer-Verlag, LNCS 2940, March 2004, pp. 49-72.

GARCIA, A.; KULESZA, U.; SARDINHA, J.; LUCENA, C.; MILIDIÚ, R. The Learning Aspect Pattern. In: Proceedings of the The 11th Conference on Pattern Languages of Programs (PLoP2004), September 8 - 12, 2004, Allterton Park, Monticello, Illinios.

CHAVEZ, C.; GARCIA, A.; LUCENA, C. Some Insights on the Use of AspectJ and Hyper/J. Proceedings of the Tutorial and Workshop on Aspect-Oriented Programming and Separation of Concerns, Lancaster, UK, August 2001


Documentation

• AspectM

• The Assessment Framework

• The Pattern LanguageGARCIA, A.; KULESZA, U.; LUCENA, C. From Objects to Agents: An Aspect-

Oriented Pattern Language. Submitted to ACM Transactions on Software Engineering Methodologies.

SANT'ANNA, C.; GARCIA, A.; CHAVEZ, C. ; LUCENA, C.; VON STAA, A. On the Reuse and Maintenance of Aspect-Oriented Software: An Assessment Framework. Proceedings of 17th Brazilian Symposium on Software Engineering, Manaus, Brazil, October 2003.

GARCIA, A.; KULESZA, U.; SANT’ANNA, C.; LUCENA, C. The Mobility Aspect Pattern. Proc. of 4th Latin American Conference on Pattern Languages of Programming, SugarLoafPLoP'04. August, 2004, Fortaleza, Brazil.

LOBATO, C.; GARCIA, A.; ROMANOVKSY, R.; SANT’ANNA, C.; KULESZA, U.; LUCENA, C. Mobility as an Aspect: The AspectM Framework. Proc. of the 1st Brazilian Workshop on Aspect-Oriented Software Development – WASP’04, SBES’04, Brasília, October 2004.


Ongoing and Future Work

• Aspect-Oriented Refactoring of Existing MASs– REFAZENDA WEBSITE. Refactoring with Aspects. URL:

http://twiki.im.ufba.br/bin/view/Aside/Refazenda

• Additional Quantitative Studies

- AspectT -Um Framework Orientado a Aspectos

para SMAs

Alessandro GarciaUirá Kulesza

{afgarcia, uira}@inf.puc-rio.br

16 Novembro, 2004

Documents

- AspectT - Um Framework Orientado a Aspectos para SMAs Alessandro Garcia Uirá Kulesza {afgarcia, uira}@inf.puc-rio.br 16 Novembro, 2004