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Lecturer

Model-Driven Development

in Practice

Prof. Dr. Kurt Geihs

University of Kassel, Germany

EECS Department

Distributed Systems

Lecturer

Name Prof. Dr. Kurt Geihs Address Distributed Systems

EECS Department

University of Kassel

Wilhelmsh?her Allee 73

D-34121 Kassel

Germany

Phone+49 561 804-6275 Telefax+49 561 804-6277

E-mail geihs@uni-kassel.de WWW www.vs.uni-kassel.de

Where we are ... http://www.vs.uni-kassel.de

Who we are ...

University of Kassel

14 Departments: Natural Sciences,

Engineering, Humanities, Art

17000 students, 320 profs, 2000 staff

EECS Faculty at University of Kassel, Germany

26 professors / 12 in Computer Science

Verteilte Systeme (“Distributed Systems”) endowed chair of Deutsche Bank and B.Braun (since 11/04) currently 1 post doc, 8 Ph.D. students, staff, students …

What we do ...

Software for Distributed Systems

Teaching

Distributed Systems, Operating Systems,

Internet Application Technology,

Software Agents …

For students of Computer Science,

Electrical Engineering, Mechatronics …

What we do ...

Software for Distributed Systems

General Research Interests

Self-management, autonomy, adaptivity in distributed systems

(e.g. context-aware adaptive mobile applications, soccer robots)

Development methodology for distributed applications

(e.g. model-driven development, genetic programming for sensor

networks)

Semantic interoperability for service-oriented architectures

(e.g. QoS-aware service brokering, service composition, service

management)

Recent Research Projects

EpisemAction

Mobile Agents for Decentralised Network

Management

Mobile Adaptive Applications Quality-Controlled Component Systems

Middleware Services for Knowledge Management

Automated Service Matching in SOA

Distributed Genetic

Programming Framework Mobile Adaptive Applications In Ubiquitous Computing Environments

Autonomous Soccer Robots

dgpf

Course Objectives

Learn about model-driven development … Why?

What is it?

What are the benefits?

How can I use it?

Where is it going to?

Literature

Copies of slides

Books

Thomas Stahl, Markus Voelter, Krzysztof Czarnecki; Model-Driven Software Development: Technology, Engineering, Management; Wiley (2006)

Michael Guttman, John Parodi; Real-Life MDA: Solving Business Problems with Model Driven Architecture; Morgan Kaufmann (2006) MDA Guide: https://www.doczj.com/doc/9f18156029.html,/mda

… many more …

Papers

additional references will be mentioned during the course

1.Motivation

2.Foundations

3.Case Study 1: Soccer Robots

4.Case Study 2: Adaptive Applications

5.Conclusions and Outlook

Reasons for Failure of S/W Projects

Lack of application domain knowledge

developer: “Love this programming tool”

Fluctuating and conflicting requirements

user: “What I say is not what I want”

Complexity of computing environment

heterogeneity, scale, dynamics, extra-functional requirements … Communication and coordination breakdowns formal specifications versus intuitive requirements

Different objectives

user versus manager versus operator versus developer

MDD is another flicker of hope to improve the situation!

Model-Driven Architecture

Co-existence of different middleware platforms CORBA, J2EE, J2ME, .NET, .NET Compact Framework, Web

Services, Message Queuing, Event-based, …

Diversity of application requirements

functional and non-functional

Heterogeneity of system environments

from Grid Computing to Ambient Intelligence

OMG proposes

Model-Driven Architecture (MDA)

( OMG = Object Management Group)

MDA-Related OMG Standards

Modelling:UML (Unified Modeling Language) UML is defined using MOF

Metamodelling: MOF (Meta-Object Facility)

standard metamodeling framework

MDA’s basic mechanism for defining various modelling lang. Model interchange: XMI (XML Meta-Data Interchange) standard way of mapping objects to XML

used to serialize UML models (import / export)

Diagram interchange

Action semantics

Models are important

Models are a must in many

engineering disciplines

architecture

mechanical engineering

...

Software models capture design information that is usually absent from code and lost during development Basis for

system generation

analysis and simulation

test generation

documentation generation

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