Automated Planning for Feature Model Configuration based on Functional and Non-Functional

Requirements

Samaneh Soltani1, Mohsen Asadi1, Dragan Gašević2, Marek Hatala1, Ebrahim Bagheri2

1Simon Fraser University, 2Athabasca UniversitySPLC’12

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Research Problem & Goal

Software development issues:Control costAccelerate time-to-marketImprove product quality

Instance1 Instance2 Instance3

Requirements1Requirements2

Requirements3

Core Software assets

Variabilities

Software Product Line Engineering

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Outline

Introduction of Software Product LineProblem StatementAutomated Feature Model Configuration

Integrating feature model with non-functional properties

Optimizing non-functional propertiesFeature model configuration using HTN planning Tooling support and evaluation

Related WorkFuture Work

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Introduction to SPLE

Software Product LineA set of similar software systems that share many common features

and satisfy the requirements of a particular domain.

Feature ModelsProvides formal and graphical representations of relations,

constraints, and dependencies of the features

FM ConfigurationSelecting best and allowable combination of features based on

objectives of stakeholder.

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Manual Feature Model Configuration

Stakeholders

Functional & Non-functionalRequirements

Root

F2F1

F4 F5 F6 F7

F3

Feature Model

Configuration ProcessApplication Engineer

Configuration Decision

Root

F2F1

F4 F5 F6 F7

F3

Final Configuration:

Roles Artifacts

Process

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Problem Statement

Research Problem:Selecting a correct set of features for one product

among all features in feature model is hard.Number of possible configuration Impact of features on non-functional propertiesStakeholders’ constraints and preferences

Solution: Using Artificial Intelligence (AI) planning technique to

select suitable features and optimize non-functional propertiesHTN planning (SHOP2)

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Overview of the Proposed Approach

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Root

F2F1

F4 F5 F6 F7

F3

Extended Feature Model

Generate Plan (using SHOP2 Planner)Application Engineer

Root

F2F1

F4 F5 F6 F7

F3

Final Product

Stakeholders

Transform to HTN formalism

Create Shop2 Domain and Problem

Constraints over NFPs

Functional Requirements

Calculate weight of NFPs and Ranks of feature using SAHP algorithm

2.

3.

1.

Requirements

Relative importance

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Extended Feature Model

NFPFeatures Security Internatio

nal SaleCustomer

Satisfaction Response

Time Cost Availability Reliability

Credit Card LowN HigP MedP 50ms $600 90% 95%

Debit Card LowP MedP MedP 60ms $450 90% 95%

Fraud Detection

HighP LowP HighP 40ms $600 80% 98%

. . .

Payment Gateway

Payment Options

Payment Type

Order Confirmation

Check out

Mail

Shipping Options

Multiple Shipments

Gift Option

E-mail PhoneElectronic Page

Fraud Detection

Cost Calculation

QoS Selection

Courier Gateway

Electronic ChecqueParadata DHLCanada

PostCyber Source

Link Point

Authorize. NET

FedexPurchase Order

Credit Card

Debit CardCash

Security [LowN]International Sale [HighP]Cost [$600]Response Time [50ms]Reliability [95%]

Security [HighP]International Sale [LowP]Cost [$600]Response Time [40ms]Reliability [98%]

Security [LowP]International Sale [MedP]Cost [$400]Response Time [60ms]Reliability [95%]

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Extended Feature Model

NFP Model:Types of NFP

Quantitative(Numeral): e.g. footprint, cost, accuracy,.. Qualitative(Ordinal): e.g. Security, reliability, integrity,..

Effect of Features Over NFPPositive e.g. securityNegative e.g. cost

Aggregation functionsAdditive,Multiplication,Min/Max, …

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Overview of the Proposed Approach

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Requirements

Constraints over NFPs

Functional Requirements

Relative importance

Root

F2F1

F4 F5 F6 F7

F3

Extended Feature Model

Generate Plan (using SHOP2 Planner)Application Engineer

Root

F2F1

F4 F5 F6 F7

F3

Final Product

Stakeholders

Transform to HTN formalism

Create Shop2 Domain and Problem

Calculate weight of NFPs and Ranks of feature using SAHP algorithm

2.

3.

1.

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Preferences & Constraints

Constraints over NFPs:Cost: $1000Ease of use: Hard Easy Very easySecurity: Low Medium High …

Preferences over NFPs:Security is slightly more important than performance (Security >3 Performance)….

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Overview of the Proposed Approach

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Calculate weight of NFPs and Ranks of feature using SAHP algorithm

1.

Requirements Root

F2F1

F4 F5 F6 F7

F3

Extended Feature Model

Generate Plan (using SHOP2 Planner)Application Engineer

Root

F2F1

F4 F5 F6 F7

F3

Final Product

Stakeholders

Transform to HTN formalism

Create Shop2 Domain and Problem

Constraints over NFPs

Functional Requirements

2.

3.

Relative importance

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Preferences

weight of each NFP calculated by SAHP algorithm

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Rank of Features

w is the weight of each non-functionalµ is average of the quantitative NFPs is standard deviation of the quantitative NFPs

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Overview of the Proposed Approach

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Transform to HTN formalism

Create Shop2 Domain and Problem2.

Requirements Root

F2F1

F4 F5 F6 F7

F3

Extended Feature Model

Generate Plan (using SHOP2 Planner)Application Engineer

Root

F2F1

F4 F5 F6 F7

F3

Final Product

Stakeholders

Constraints over NFPs

Functional Requirements

Calculate weight of NFPs and Ranks of feature using SAHP algorithm

3.

1.

Relative importance

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SHOP2 Domain and Problem

HTN Planning Problem P =(s0 , T0 , D)

Basic Elements of a Domain Descriptiona set of operators o ∈ Oa set of tasks a ∈ Aa set of methods m ∈ Ma set of domain predicates v V∈

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operator

Transforming Feature Model to HTN

operator

operatoroperator operator

Feature2

Atomic FeatureAtomic FeatureAtomic Feature

Atomic Feature

Feature1

Feature4

Atomic FeatureAtomic FeatureAtomic Feature

Feature3

task & method(s)

operatoroperator operator

Atomic Feature

task & method(s)

task & method(s)

task & method(s)

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Transforming Feature Model to HTN

Domain predicate transformationOperator transformation Method and task transformation

Preprocessing step

f

f1 fo

f

f1

fo f d

fp

f

f1 f2

(a) (b)

f

f1 f2

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Generating Domain Predicates:

f

f2f1

f3 f4 f5

NFPQT1

QT2

QT3

Domain Predicates for leave features:vf3, vf4, vf5, vf2

Attainment Formula for intermediate

features:f1 = vf3 vf4 vf5 f = f1 vf2

Domain Predicate for Qualifier Tags:vQT1, vQT2, vQT3

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Generating Operators Operators for atomic features: of 2, of 3, of 4

pre(of 2 ) = MaxCost - f2Cost>0

eff(of 2) = ,

(MaxCost = MaxCost - f2Cost) value(of 2) =

pre(of 3 )= QT2 vf 4 eff(of 3)=vf 3 value(of 3 )= 1.5

pre(of 4 )= QT3 vf 3

eff(of 4) = vf 4

value(of 4) = 0.75

f

f4f1

f2 f3

Required

Exclude

QT3

Value=0.75

QT1, QT3Value=0.5

f2Cost = $98

QT2

Value=1.5

MaxCost(Requested by stakeholder )= $1000

QT1 QT3 vf 4

vf2

0.5

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Generating Tasks and Methods (AND)

Task: tf

One method mf for feature f with

Tsk-mf = tf Pre-mf = f6 f7

Dec-mf = {of1, tf2}

f

f1 f2

f6

f7

Required Exclude

......

...

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Generating Tasks and Methods (XOR)

Task: tf

methods m1f , m2

f for task tf with:Tsk-m1f = tf , Pre-m1f = f 6 f 7 ,

Dec-m1f = {of 1 }

Tsk-m2f = tf , Pre-m2f = f 6 f 7 ,

Dec-m2f = {tf 2 }

f

f1 f2

f6

f7

Required Exclude

......

...

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Task: tf

One method mf for feature f withTsk-mf = tf

Dec-mf = {tf1_o , tf2_o , of_or}

Tsk-m1f1_o = tf1_o Tsk-m2

f1_o = tf1_o , Dec-m1

f1_o = {of 1 } Dec-m2f1_o = {of d }

Tsk-m1f2_o = tf2_o , Tsk-m2

f2_o = tf2_o Dec-m1

f2_o = {tf 2 } Dec-m2f2_o= {of d }

Pre(of _or )= vf 1 f 2

Generating Tasks and Methods (OR)

f

f1 f2

(c)

... f

f1_o f2_o

...

f1fd f2 fd

for

Pre processing step

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Generating FM Configuration

Root

F2F1

F4

F5

F6 F7

F3

Final Product

Generate Plan (using SHOP2 Planner)

Create Shop2 Domain and Problem

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Tooling Support

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Evaluation

RQ1 (Scalability): Can the approach configure feature models, in a reasonable time?independent variables

number of featuresnumber of constraintsintegrity constraints

dependent variabletime

RQ2 (Effectiveness): How effective is the approach in producing a feature model configuration?

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Evaluation (1)

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Evaluation (2)

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Comparative Analysis of Related Works

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Conclusion

Integrating the feature model and non-functional properties

Facilitating the feature model configuration process by automating the feature model configuration process

based on non-functional requirements;Employing visualization and interaction techniques

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Future Work

Using other HTN plannerPDDL and PDDL based plannerEmploying more interaction and visualization

techniques

Thanks!masadi@sfu.ca

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