Markus Völter voelter@acm voelter.de

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MDSD Intro & Overview

Markus Vö[email protected]

Model-DrivenSoftware Development

Introduction and Overview

www.mdsd-buch.de

www.mdsd-book.org



Domain Driven Development

• Domain Driven Development is about making software development more domain-related as opposed to computing related. It is also about making software development in a certain domain more efficient.

Software TechnologyConcepts

Domain Concepts

Software TechnologyConcepts

Domain Concepts

mental workof developers



How MDSD works

• Developer develops model(s)based on certain metamodel(s), expressed using a DSL.

• Using code generation templates, the model is transformed to executable code.• Alternative: Interpretation

• Optionally, the generated code is merged with manually written code.

• One or more model-to-model transformation steps may precede code generation.

ModelModelModel

Transformer TranformationRules

Model

TransformerCode

GenerationTemplates

Generated CodeManuallyWrittenCode

optional

Metamodel

Metamodel

optio

nal,

can

be

repe

ated



Reasons for DDD

• Software Development is too complex and too expensive (now, this is a really new finding ) …

… because:• There is too little reuse• Technology changes faster than developers can learn • Knowledge and practices are hardly captured explicitly

and made available for reuse• Domain experts cannot understand all the technology

stuff involved in software development

• DDD aims at attacking some of these problems.We shall see how on the following slides.



What is a „Domain“

• A definition could be:

A domain is a bounded area of knowledge or interest.

• Examples (from the world of Software) include:• eBanking• Embedded Software• Web-Based eBusiness Applications• Control Software for 4-Cylinder Diesel Engines• Astronomical Image Processing Software

• Domains can have varios „scopes“ as well as various „flavours“ – see next slides.



Hierarchical Structuring of Domains

• Since Domains can be of any size or granularity, it is useful to structure domains hierarchically.

• Automotive Example:

• eBanking Example:

EmbeddedSystems

AutomotiveSystems

Engine Controllers

Diesel Gasoline4-Cyl

eBusinessApps

web-based

RichClients

e-Banking

moneytransfer

inv.bank.



„Kinds“ of Domains

• In the context of software development it is also useful to distinguish (at least) two kinds of domains:

• Technical Domains adress key technical issues related to software development such as•Distribution, Failover and Load-Balancin•Persistence and Transactions•GUI Design•Concurreny and Realtime

• Functional Domains represent the business/professional issues; examples include•Banking•Human resource management• Insurance•Engine Controllers•Astronomical Telescope Control



MDSD Core Concepts

Model

DomainSpecific

Language

Metamodeltextual

graphical

Domain

Ontology

bounded area ofknowlege/interest

semantics

precise/executable

multiple

partial

viewpoint

subdomains

composable

Metametamodeltarget

softwarearchitecture

softwarearchitecture

transform

compile

interpret

multi-step

single-step

noroundtrip

knowledge

several

designexpertise



Example 1: Model and Metamodel

interface Sensor { operation start():void; operation stop():void; operation measure():float;}interface Controller { operation reportProblem(Sensor s, String errorDesc ):void;}

*

{ordered}Interface

name : Stringtype : String

Operation

name : Stringtype : String

Parameter

type : String

Exception**



Example 2: Model (J2ME apps)

NumberEntryForm

a: Number ["a"] {a>0}b: Number ["b"] {b>0}

CalcResultDisplay

["The Result is "+c]{align=center}

["Abort"]

["Result"]

>> a,b c: Number;c = a + b

>> c

["Again"] ["Exit"]



Example 2: Metamodel (J2ME apps)

name : String

UIElement

Form

label : Stringconstraints: String

Display

varName : Stringlabel : Stringconstraints: String

Field

Flow

transportedVars: String

AutoFlow

label : StringtransportedVars: String

Button

Element

Start End

declaredVars: Stringexpression : String

Calculation

1 to

1 from

outbound*

inbound*

Example 3: Model (Components, Ports, Connectors)<system name=”weatherStation”> <node name=”main”> <container name=”main”> <instance name=”controller” type=”Control”/> </container> </node> <node name=”inside”> <container name=”sensorInside”> <instance name=”tempInside” type=”TemperatureSensor”>´ <param name=”unit” value=”centigrade”/> </instance> </container> </node> <node name=”outside”>…</node>

 <connector name="toSensorTempOutside"> <providedPort instance="tempOutside" port="measurementPort"> <requiredPort instance="controller" port="sensorsPort"> </connector> <connector name="fromSensorTempOutside"> <providedPort instance="controller" port="controllerPort"> <requiredPort instance="tempOutside" port="controllerPort> </connector>  <connector name="toSensorHumOutside">…</connector> <connector name="fromSensorHumOutside">…</connector>  <connector name="toSensorTempInside">…</connector> <connector name="fromSensorTempInside">…</connector></system>



Example 3: Metamodel (Components, Ports, Connectors)

*

ComponentRef

name : String

ComponentInstance

1

System Node* *Connector

Type

1 type

DirectCallConnector

SharedMemoryConnector

CANConnector

{open}

ProvidedPortRef

RequiredPortRef

id : String

Connector

1 1source target

*

context Connectorinv: source.interface == target.interface

Container

*



Example 4: Workflow Model (UML + Stereotypes)

+ verfuegbarkeitPruefen( reservierungsBeginn : Date, reservierungsEnde: Date, gewaehlteStationID : String, gewaehlteKfzKlasseID : String ) : Collection

+ getReservierungsParameter() : ReservierungsParameterVO

+ kfzReservieren( reservierungsBeginn : Date, reservierungsEnde: Date, gewaehlteKfzNr : String, mitgliedsNr : String ) : ReservierungBestaetigenVO

<<ProcessObject>>ReservierungDurchfuehrenPO

- Mitglied : String- Station : String- Kfz : String- ReservierungsBeginn : Date- ReservierungsEnde : Date

<<ValueObject>>ReservierungBestaetigenVO

- stationen : Collection- kfzKlassen : Collection

<<ValueObject>>ReservierungsParameterVO

- ReservierungsBeginn : Date- ReservierungsEnde : Date- Station : String- KfzKlasse : String- KfzBezeichnung : String- KfzNr : String

<<ValueObject>>VerfuegbarkeitPruefenVO



Example 4: Workflow Model II (UML + Stereotypes)

+ AnmeldungErfolgreich() : Boolean

<<ActivityController>>BenutzerAnmeldenCtrl

+ Weiter()+ Ende()

- kennung : String- passwort : String

<<Presentation>>BenutzerAnmelden

- Name : String- Passwort : String- Kennung : String

<<ValueObject>>BenutzerAnmeldenVO

benutzerAnmelden( kennung : String, passwort : String ) : BenutzerAnmeldenVO

<<ProcessObject>>BenutzerAnmeldenPO

- <<Key>> Name : String- Passwort : String- Kennung : String

<<EntityObject>>Benutzer



Example 5: Power Grid

SomePlace: Generator

G11: GenerationElement

20KV: Bus

link11

T11: Transformer

link12

220KV: Buslink13end11

link14

SomeOtherPlace: SwitchingStation

end21

transmissionLine1

B21-220KV: Bus

link21

B22-10KV: Bus

T21: Transformer

link22

link23

link24

end22

SomePlace:Generator

SomeOtherPlace:SwitchingStation

end11 end21 end22

transmissionLine1



Example 5: Power Grid Metamodel

GenerationElement

MicroNode Link1 targetNode sources 0..*

1 sourceNode targets 0..*

Transformer Bus Endpoint

MacroNodeTransmission

Line

1 targetNode sources 0..*

1 sourceNode targets 0..*

0..*parts

Generator BranchPoint SwitchingStation

sourceEndPoint 1 1 targetEndPoint

targetTransmissionLine 0..1 0..1 sourceTransmissionLine



MDSD Core Values

• We prefer to validate software-under-construction over validating software requirements

• We work with domain-specific assets, which can be anything from models, components, frameworks, generators, to languages and techniques.

• We strive to automate software construction from domain models; therefore we consciously distinguish between building software factories and building software applications

• We support the emergence of supply chains for software development, which implies domain-specific specialization and enables mass customization



MDSD Core Building Blocks

• domain analysis

• meta modelling

• model-driven generation(and: model transformation)

• template languages

• domain-driven framework design

• the principles for agile software development

• the development and use of Open Source infrastructure



MDSD and Requirements/Analysis

• An often-asked question is: are MDSD models the same as requirements/analysis models?• They can be, but in general, they

are not.• Analyis/requirements models

are non-computational, MDSD models are compuatational.

somewhere the „intellectual work of development and problem solving“ has to be put into the system. Usually, this is on the stage from requirements/analysis to (computational) MDSD models.

• How can MDSD help with requirements?• Formalizing Requirements using a DSL is benefitial

because requirements become unambigious.

Model

SystemModel

Business Model(Domain Model)

LogicalModel

Physical Model(Deployment)

RequirementsModel

ComputationalModel

PIM PSM

Adap

ted

from

Fra

nkel

‘s b

ook

on M

DA



MDA and Model Driven Software Development Overview

Model

DomainSpecific

Language

Metamodeltextual

graphical

Domain

Ontology

bounded area ofknowlege/interest

semantics

precise/executable

multiple

partial

viewpoint

subdomains

composable

Metametamodel

transform

compile

interpret

multi-step

single-step

noroundtrip

UML+Profiles

MOF

OCL, Action Semantics

PIM, PSM, .... QVT

several targetsoftware

architecturesoftware

architecture

Applicationdesignexpertise

• Focus: Platform Independence, (Tool) Interop



Other related approaches

• Microsoft’s Software Factories:Focus on Reuse, Efficient Development, DSLs

• Domain-Specific (Visual) Modelling:Focus on (Visual) DSLs

• Generative Programming:Focus on Efficiency, “Automatic Manufactoring”, Software System Families

• Language-Oriented Programming:Focus on DSLs instead of Frameworks, incl. Editor/Debugger Support

all basically the same



MDSD and Agility

• Agile Manifesto:We are uncovering better ways of developing software by doing it and helping others do it. Through this work we have come to value: - Individuals and interactions over processes and tools - Working software over comprehensive documentation - Customer collaboration over contract negotiation - Responding to change over following a plan That is, while there is value in the items on the right, we value the items on the left more.

• MDSD-Models are no „paperwork“, they are the code which is translated to code automatically

• Agility does not oppose tools in general – compilers are ok, model transformers are a kind of compiler



MDSD and Agility II

• Project automation (ant, cruisecontrol) is ok in „agile minds“, so is automation of the writing of repetitive code

• Automation of the development process makes responding to change easier and faster (single source principle). • Changes in the model respond to changes in the functional

requirements• Changes in the templates/transformations can be used to

evolve the architecture

• The customer on-site can be integrated better, if we have languages that are better related to domain concepts as opposed to 3GL code or the like.• Pair programming between developer and domain expert is

more realistic.



MDSD and Agility III

• Tests can still be written manually (even before generation), generators can help is building mocks or scenarios

• We do not recommend a waterfall that first builds generators and then builds apps, rather, both are iteratively evolved in parallel. • Domains Architectures are based on experience, not

based on „big design upfront“

• Developers can do what they can do best:• Some deal with applications and customer requirements,• Others deal with technical architecture, platforms and

generators

• So: There is no problem with Agility and MDSD!



Reasons for using MDSD

• You want to provide a way for your domain-experts to formally specify their knowledge, and to provide a way for your technology people to define how this is implemented (using model transformations).

• You might want to provide different implementations (i.e. more concrete models) for the same model, perhaps because you want to run it on different platforms (.NET, Java, CORBA).

• You may want to capture knowledge about the domain, the technology, and their mapping in a clear, uncluttered format.

• In general, you don’t want to bother with implementation details when specifying your functionality.

• MDSD results in a fan-out, i.e. one set of models can be the source for transformations to several targets.

• Another reason for using MDSD: You are working in the context of product lines and software system families and need to develop domain-specific assets.



MDSD Benefits I

• Models are free of implementation artifacts – they directly represent domain knowledge and are thus reusable.

• Implementations for various platforms can be generated in principle – the technology change problem is adressed to some extend.

• Technology freaks and domain experts can take care of „their business“ (transformations and models, respectively) and need to care of each other‘s problems only in a limited way.

• Domain experts can play a direct role in development since they can more easily understand models expressed with a DSL as opposed to implementation code.

Domain Experts play the central role they deserve!



MDSD Benefits II

• Development becomes more efficient since repetitive implementation code can be generated automatically.

• Architectural contraints/rules/patterns can more easily be enforced, since the they are embedded in the templates rather than just being documented (and ignored).

This is especially important in really large teams, often in the context of Product-Line Engineering and Software System Families.

• Transformer/Generator can address cross-cutting concerns (just like an aspect weaver)



MDSD Predjudices

• MDSD does not require UML – any kind of modelling language is ok, graphical or textual

• Precise and complete models…• … are not the the same as „visualized code“ – the

abstraction level is higher• … are not the same as analysis models – analysis models

are not computational

• MDSD does not require – not even recommend – a waterfall. Development of the generative infrastructure is iterative and incremental.

• You do not need big and expensive tools – a lot of small and useful open source tools are available.

• You don‘t need to generate 100% of the code – it is ok, to also code some aspects in a 3GL.



Benefits for Software Quality

• MDSD requires an explicit, well-defined architecture. Defining an architecture this way improves the quality of the system (indpendent of whether it is generated or not).

• Transformations capture expert knowledge. The generated code reflects this expert knowledge uniformly.

• An Domain Archtitecture defines a strict programming model for the manually developed parts – again, uniformity and constrained-ness improves quality.

• Generator does not produce accidental errors – either things are always right or always wrong. This makes finding errors easier!

• Models can serve as an up-to-date and always current documentation.



Benefits for Software Quality II

• In general, MDSD forces you to take care of many good things, which you‘d like to have in any application development project:

• Domain/Application Scoping

• Variability Management

• Well-Defined Software Architecture, Architecture Metamodelling

• Trying to build a generator for a domain/target architecture enables your understanding of the domain/target architecture. This in itself is a huge benefit.



No Free Lunch - Challenges

• You need additional skills in your team (domain analysis , metamodelling, generator development, architecture)

You need a couple of good people who usually aren‘t easy to get, and who aren‘t cheap.

• Your development process needs to reflect the two-track nature of MDSD (domain architecture development, application development)

• Sometimes tools require some „creative use“ and improvisation ( use open source!)

• Remember: a fool with a tool is still a fool

generator



MDSD (compared to “normal” Software Development)

Level of Detail

Result ofAnalysis

virtual or realImplementation model Implementation

Info

rmat

ion

Gai

n

Start

GoalImplementation

Analysis

Design

Effort



MDSD Effort (stage 1)

Level of Detail

Results ofAnalysis

virtual or realimplementation model Implementation

Info

rmat

ion

Gai

n

Start

GoalImplemen-

tation

Analys

is

Effort

Modell

ing

Automation

Savings based onthe use of a semantically

rich platform

Savingsbecause

of Generation

A

A' B



MDSD Effort (stage 2)

Level of Detail

Results ofAnalysis

virtual or realimplementation model Implementation

Info

rmat

ion

Gai

n

Start

Goal

Analy

sis

Effort

Mod

ellin

g

Automation

Savings based onthe use of a semantically

rich platform

Savingsbecause

of generation

A

BA'



Some advertisement

• For those, who speak(or rather, read) german: Völter, Stahl: Modellgetriebene SoftwareentwicklungTechnik, Engineering, ManagementdPunkt, 2005www.mdsd-buch.de

• A very much updated translation isunder way:Model-Driven Software Development, Wiley, Q2 2006www.mdsd-book.org

Update currently in progress,

with Arno Haase and Sven Efftinge as

additional coauthors

Markus Völter voelter@acm voelter.de

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