06 goal modeling

7/21/2019 06 Goal Modeling

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2006-07 Betty H.C. Cheng. This presentation is available free for non-commercial use with attributionunder a creative commons license.

Goal Modeling

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We Will Cover

What is a goal? Where do goals come from?

What is a goal model?

When to use goal models? How do goal models relate to UML models?

Why use goal models?

Capturing the goal model

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What is a goal?

A stakeholder objective for the system The system includes the software and its

environment

Who are stakeholders?

Anyone who has an interest in the system Customers, end users, system developers,

system maintainers...

What is a goal model?

A hierarchy of goals

Relates the high-level goals to low-level systemrequirements


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Goal or Not a Goal?

Goal Examples: Credit card information is kept private

Credit card information is accurate

Safe transportation

Highly reliability

Non-goal Examples: The system will be implemented in C++

The paint colors for the cars will be yellow,orange, and red

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Goal Exercise

Order the list of goals from high-levelconcern to low-level concern

User receives a request for a timetable from asystem

Collect timetables by system

Schedule meeting

System collect timetables from user Collect timetables


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Goal Exercise

Order the list of goals from high-levelconcern to low-level concern

Schedule meeting

Collect timetables

Collect timetables by system

System collect timetables from user

User receives a request for a timetable


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Types of Goals

Functional (Hard) Describe functions the system will perform

Well defined criteria for satisfaction

E.g., System collects timetables from user

Non-functional (Soft or fuzzy) Describe desired system qualities

Hard to define; satisficed rather than satisfied

Reliability E.g., System should be reliable

Quality E.g., System should be high quality.


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Where do goals come from?

Conveyed by stakeholders Disclosed in requirements documents

Analysis of similar or current system

Elaborating other goals


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Goal Exercise

Identify goals in the following paragraph An Adaptive Regional Forecasting Ecological Observatory (ARFEO) is proposed asmeans to implement an operational, run-time configurable, and adaptable ecologicalobservatory to be used for regional ecological forecasting. ARFEO has three maindimensions. First, using a holistic perspective of environment, we will use sensorsthat are analogous to human and organism senses to monitor the environment and itschanges. As such, ARFEO can be configured to observe and answer ecologicalquestions specific to one class of sensory input or across multiple sensory inputs.

Second, ARFEO will use a cyberinfrastructure comprising smart, heterogeneoussensor networks, small-scale and GRID-scale distributed computing [6]. ARFEOsarchitecture will be a distributed design which will enable users to perform small andcomplex computations and transparent integration of data and analysis. ARFEO willenable a user to adapt monitoring capabilities at run-time, thus allowing a user tocustomize the configuration to specific needs and questions. Finally, ARFEO willemphasize the reuse and synergistic integration of existing analysis and visualizationtechniques to include in the computational toolkit for processing the sensor andancillary data, as well as metadata. A key part of ARFEO will be the development of

processes to make use of the toolkit element to support the analysis and visualizationcapabilities.


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When to use goal models

Early requirements engineering Focus on identifying problems

Exploring system solutions and alternatives

Done before UML modeling

Design Code TestLate REEarly RE

Why? What? How?


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Why use goal models?

Give rationale for requirements Identify stable information

Guide requirement elaboration


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The Goal Model


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Running Example

Meeting Scheduler Assists the initiator in scheduling a meeting

Meeting should be convenient for participants

Participants should be available

Modeled using the i* goal notation

13Example adapted from the RE06 keynote given by John Mylopoulos


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Goal Model

Chooseschedule

Schedule

meeting

Collecttimetables

Bysystem

Byperson

Collect fromagents

Collect fromusers

Receive

requestSend

request

Manually Automatically

Goals are refined into

subgoals that elaboratehow the goal is

achieved

Example adapted from the RE06 keynote given by John Mylopoulos


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AND Refinement

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Chooseschedule

Schedule

meeting

Collecttimetables

Bysystem

Byperson

Collect fromagents

Collect fromusers

Receive

requestSend

request


AND

AND AND

AND

All of the

subgoals must beachieved for the

goal to beachieved



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OR Refinement

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Chooseschedule

Schedule

meeting

Collecttimetables

Bysystem

Byperson

Collect fromagents

Collect fromusers

Receive

requestSend

request


AND

ANDAND

OR OR

OR OR

OR OR

AND

At least one of the

subgoals must beachieved for the

goal to be achieved



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Interpretations of OR Refinements

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Chooseschedule

Schedule

meeting

Collecttimetables

Bysystem

Byperson

Collect fromagents

Collect fromusers

Receive

requestSend

request


AND

ANDAND

OR OR

OR OR

OR OR

AND

Static systems-alternative solutions

Adaptive systemspoints of variation



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Softgoals

Minimal

conflicts

Good Qualityschedule

Goodparticipation

Collection

effort

Matchingeffort

Minimaleffort

Minimaldisturbances

Accurateconstraints

AND

AND

AND

AND



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Modeling Softgoals

Used to evaluate alternatives Helps (+)

Makes (++)

Hurts (-) Breaks (--)



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Contributions to Softgoals

Chooseschedule

Schedulemeeting

Minimal

conflicts


Goodparticipation


AND

OR

OR

!

+

+

!

AND

AND



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Construction Process

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Minimal

conflicts


Goodparticipation

Minimaldisturbances

Accurateconstraints

Collectioneffort

Matchingeffort

Minimal

effort

AND

AND AND

AND

1. DefineSoftgoals


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2. DefineHardgoals

Steps 1 & 2may be

iterative

Schedulemeeting

Collecttimetables

Bysystem

Byperson

Collect fromagents

Collect fromusers

Receive

requestSend

request

Minimal

conflicts


Goodparticipation

Minimaldisturbances

Accurateconstraints

Collectioneffort

Matchingeffort

Minimal

effort

Chooseschedule


AND

ANDAND

OR OROR

OR OR

OR

AND

AND

AND

AND

AND

22Example adapted from the RE06 keynote given by John Mylopoulos



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2006-07 Betty H.C. Cheng. This presentation is available free for non-commercial use with attributionunder a creative commons license.23

Schedulemeeting

Collecttimetables

Bysystem

Byperson

Collect fromagents

Collect fromusers

Receive

requestSend

request

Minimal

conflicts


Goodparticipation

Minimaldisturbances

Accurateconstraints

Collectioneffort

Matchingeffort

Minimal

effort

Chooseschedule


AND

ANDAND

OR OROR

OR OR

OR

+

!

!

+

!

+

+

!

!

+

!

+

AND

AND

AND

AND

AND



3. Evaluatehardgoalcontributionto softgoals


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Integrating Goals with Other

Models

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Integrated Use of Goals

KAOS Refining goals into requirements

4 models Goal

Agent Operationalization

Object


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KAOS Goal Model

Agent - active system component

Object - inactive system component

Operation - an action an agent takes to achieve a goal

Requirement - a goal for which an automated component is responsible

Expectation - a goal for which a human is responsible Safe Transportation

Maintain Knowledge of Other Train Locations

Manually Radio Other Train Conductors

Radio Automatically Sense Other Train Locations

TrainRadio Other Train

SoftwareSensor

Human


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KAOS Goal Model










SoftwareSensor

Human


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KAOS Goal Model










SoftwareSensor

Human


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KAOS Goal Model










SoftwareSensor

Human


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KAOS Goal Model










SoftwareSensor

Human


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KAOS Goal Model










SoftwareSensor

Human


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KAOS Goal Model










SoftwareSensor

Human


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KAOS Goal Model










SoftwareSensor

Human


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KAOS Goal Model










SoftwareSensor

Human


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KAOS Goal Model










SoftwareSensor

Human


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KAOS Goal Model










SoftwareSensor

Human


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KAOS Agent Model

Objective: depicts agent responsibilities Agent models can be inferred from goal models

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Sensor



Automatically Sense Other Train Locations


SoftwareSensor

Human


Software

Human

Goal Model Agent Model


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KAOS Agent Model


27

Sensor





SoftwareSensor

Human


Software

Human

Human




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KAOS Agent Model


27

Sensor





SoftwareSensor

Human


Software

Human



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KAOS Agent Model


27

Sensor





SoftwareSensor

Human


Software

Human


Alert Passengers to Delays

Human

Manually Slow the Train



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KAOS Agent Model


27

Sensor





SoftwareSensor

Human


Software

Human



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KAOS Operationalization Model Objective: specifies the operations that agents must

perform to achieve the goals

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Door

Safe Transportation

Train Doors Closed While Moving

Train Begins to Move

Close Door

Close Door Request


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KAOS Operationalization Model Objective: specifies the operations that agents must

perform to achieve the goals

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Door

Safe Transportation



Close Door

Close Door Request

Door



Close Door


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KAOS Object Model

Objective: further specifies objects used in the goal model The syntax is similar to a that of a UML class diagram

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TrackSegment

SpeedLimit

Gate

Loc

Status

Switch

position

Speed

Loc

Train

Track

hasGateOn

On Track

Following


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Integrated Use of Goals

KAOS Refining goals into requirements

4 models Goal

Agent Operationalization

Object

i* Relates goals to the organization context

2 models Actor (Strategic) Dependency Model

Actor (Strategic) Rationale Model


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i* Actor Dependency Model

Dependencies between actors - An actor is a black box

31Diagram from Towards Modelling and Reasoning Support for Early-Phase Requirements Engineeringby Eric Yu

D

MeetingInitiator

ProposedDate(m)

Agreement(m,p)

AttendsMeeting(ip,m)

Assured(AttendsMeeting(ip,m))

AttendsMeeting(p,m)

MeetingBeScheduled(m)

MeetingScheduler

Important

Participant

X

ISA

DD

DD

D

DD

D

D D

DD

D

D

D

EnterDateRange (m)

Enter

AvailDates (m) Meeting

Participant

D

D

D

D

D

D

D

D

Depender Dependee

LEGEND

O XOpen (uncommitted) Critical

Resource Dependency

Task Dependency

Goal Dependency

Softgoal Dependency


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D

MeetingInitiator

ProposedDate(m)

Agreement(m,p)



AttendsMeeting(p,m)


MeetingScheduler

Important

Participant

X

ISA

DD

DD

D

DD

D

D D

DD

D

D

D

EnterDateRange (m)

Enter


Participant

D

D

D

D

D

D

D

D

Depender Dependee

LEGEND


Resource Dependency

Task Dependency

Goal Dependency

Softgoal Dependency

D

D

D

D

D

D

D

D

Depender Dependee

LEGEND


Resource Dependency

Task Dependency

Goal Dependency

Softgoal Dependency


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D

MeetingInitiator

ProposedDate(m)

Agreement(m,p)



AttendsMeeting(p,m)


MeetingScheduler

ImportantParticipant

X

ISA

DD

DD

D

DD

D

D D

DD

D

D

D

EnterDateRange (m)

Enter


Participant

D

D

D

D

D

D

D

D

Depender Dependee

LEGEND


Resource Dependency

Task Dependency

Goal Dependency

Softgoal Dependency


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i* Actor Rationale Model

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Internal actor relationships - An actor is a white box

Agreeable(Meeting,Date)

AgreeToDate

Convenient(Meeting,Date)

ProposedDate

Agreement

ObtainAgreement

ObtainAvailDates

FindAgreeable Slot

MergeAvailDates

Quick MeetingBeScheduled

ScheduleMeeting

AttendMeeting

ParticipateInMeeting

LetScedulerScheduleMeeting

ScheduleMeeting

MeetingInitiator

MeetingSchedulerMeetingBe

Scheduled

FindAgreeableDateUsingScheduler

FindAgreeableDateByTalking

ToInitiator

Quality(ProposedDate)

UserFriendly

ArrangeMeeting

RicherMedium

Enter

AvailDates

OrganizeMeeting

MeetingParticipant

AttendsMeeting

EnterDateRange

D

D

D

D

DD

D D

DD

D

D

+ !

!

+

+

!

+

+! +

+

LEGEND

Goal

Task

Resource

Soft!Goal

Task!Decompo! sition linkMeans!ends link

Contribution to softgoalsActor

Actor Boundary

+!

LowEffort

LowEffort

Diagram from Towards Modelling and Reasoning Support for Early-Phase Requirements Engineeringby Eric Yu


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i* Actor Rationale Model

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Internal actor relationships - An actor is a white box


AgreeToDate


ProposedDate

Agreement

ObtainAgreement

ObtainAvailDates

FindAgreeable Slot

MergeAvailDates


ScheduleMeeting

AttendMeeting



ScheduleMeeting

MeetingInitiator


Scheduled



ToInitiator


UserFriendly

ArrangeMeeting

RicherMedium

Enter

AvailDates

OrganizeMeeting

MeetingParticipant

AttendsMeeting

EnterDateRange

D

D

D

D

DD

D D

DD

D

D

+ !

!

+

+

!

+

+! +

+

LEGEND

Goal

Task

Resource

Soft!Goal



Actor Boundary

+!

LowEffort

LowEffort

Diagram from Towards Modelling and Reasoning Support for Early-Phase Requirements Engineeringby Eric Yu

LEGEND

Goal

Task

Resource

Soft!Goal


Contribution to

softgoalsActor

Actor Boundary

+!


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AgreeToDate


ProposedDate

Agreement

ObtainAgreement

ObtainAvailDates

FindAgreeable Slot

MergeAvailDates


ScheduleMeeting

AttendMeeting



ScheduleMeeting

MeetingInitiator


Scheduled



ToInitiator


UserFriendly

ArrangeMeeting

RicherMedium

Enter

AvailDates

OrganizeMeeting

MeetingParticipant

AttendsMeeting

EnterDateRange

D

D

D

D

DD

D D

DD

D

D

+ !

!

+

+

!

+

+! +

+

LEGEND

Goal

Task

Resource

Soft!Goal



Actor Boundary

+!

LowEffort

LowEffort

06 goal modeling

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