presentation given at the ESI Symposium 2009 (Eindhoven, The Netherlands); abstract: http://www.esi.nl/events/esi_symposium_2009/programme/2_1_abstract.html

1. Modeling: the holy grail for designing
complex systems?
Teade Punter (ESI)
Roelof Hamberg (ESI)
Hristina Moneva (ESI)

2. Aspects of reality
• Multiple formalisms are needed to answer specific
questions
• Typical problem: Not feasible to model the complete system
• Typical problem: Not all users have the latest version of the
system
• Typical problem: What are the implications to the rest of the
system
• How to connect these tools / models in generic way and provide
early flaw detection?
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3. Aspects of reality
• Concurrent engineering
• Typical problem: Not keeping track of design decisions
• Typical problem: Not explicit enough to the rest of the team
• Typical problem: What are the implications to the rest of the
system => which components are affected
• Typical problem: Forget to re-run some experiments => not
consistent results
• How to provide model and result history related to the design
decisions taken?
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4. Aspects of reality
• Not feasible to model the complete system
• Typical problem: It is not cost effective to model the complete
system
• Boderc: only ~10% of the system is being modeled
• How to connect models which cover different parts of the same
system?
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5. Belief
IDEAL CURRENT
FUTURE REALITY
MAKING THE IMPLICIT
EARLY FLAW
EXPLICIT  BRIDGING
DETECTION
THE GAP!!!
MAINTAIN DESIGN CONCURRENT
CONSISTENCY ENGINEERING
IMPROVED DESIGN MULTIPLE
QUALITY FORMALISMS
NOT FEASIBLE TO
SHORTENINGOVERALL
MODEL THE COMPLETE
DESIGN PROCESS
SYSTEM
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6. Design methodology for high-tech systems
the world
Preparation
market opportunity
drivers
identify key drivers critical realization
& requirements aspects
State of technological
opportunity
changes
the Art
realization options
key requirements
consolidate
data, models, experience
core domain
changes
know-how
rules, models,
no-brainers
data, solutions
Selection of critical aspects questions Evaluation of design options
explanation
open
identify
questions gather facts & build small perform
tensions and
uncertainties models measurements
conflicts
answers verification
decisions decisions
Design specifications Record Design decisions
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07/12/200

7. Modeling: the holy grail for designing
complex systems?
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8. Requirements for Integration Framework
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9. Integration Framework overview
• Basic concepts and assumptions:
• Design flow
• Design step
» View
» Components
» Model
• Design decision
• Integration Framework should
support:
• Basic element representation
• Populating dependencies
• Conflict detection
• Design process representation
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10. Integration Framework basic blocks
• Model:
• From “drawing on a napkin” to
“model to model transformations”
• May be part of multiple components /
views formalism
accuracy
credibility
• May be used for analysis working range
• Parameters: structure/abstraction
• May have range, type, unit facts model decision taking
OUTPUT
INPUT
• Represent: errors
assumption verification
unknown measurements analysis specification
» Assumptions uncertainties
» Measurements
» Requirements tool tool tool tool
» Etc.
• May have dependencies
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11. Integration Framework basic blocks
• View:
• Representation of an aspect at
system level
• System decomposition & parameter environment VIEW
dependencies system
• Multiple models per component
• Multiple experiments per model
• Design step: M
M
• Multiple views M
M
• Hierarchy of components M M
• Multiple models per component
• Completeness of modeling:
• “Boderc”
• ~10%
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12. Integration Framework basic blocks
• Design flow: design option
design option
• Decisions DS design decision DS
– Design decision
design option
assure/predict
– Design options (alternatives) qualities
• Refinement
• Process independent:
• Keeps track of design decisions
• Provides model / result management
DS
DD
DS
DD DD
DS DS DD DS DD DS
DD
DS
DS – design step
DD – design decision
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13. Prototype DSL
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14. Prototype DSL: textual editor
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15. Integration Framework features
• Populating
dependencies
• One or multiple
views
• Conflict detection
• One or multiple
views
• In previous design step
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16. Prototype VIEW: graphical editor
BASIC BLOCK
ADD PROPERTY / MODEL
ONLY IF NEEDED!
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17. Prototype VIEW: graphical editor
PROPERTY HAS
VALUE, UNIT
RANGE
DEPENDENCY
MODEL HAS
FILE
EXPERIMENT CONFLICT DETECTION
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18. Integration Framework features
DD1: add ... DD2: continue
DS0 DS1
(iteration 1) developing...
• Multi-user (team) design process
DS0 DD1 DS1 DD2 DS2
DO1
• Reuse of components
DD3 DS3 DD4 DS4
DO2
Team A
DS0 DD1 DS1
DD2 DS2
Team B
PRODUCT
NEW
DD1: add “System A” DD2: continue DS0 DD1 DS1 DD2 DS2
DS0 DS1
as component developing...
DD3 DS3 DD4 DS4
re
us
e Team C
BRANCH MERGE
REUSED COMPONENT
DS2
DD2
DS0 DD1 DS1
DD3
DO1
DS3 DD4 DS4 DD5 DS5
DO2
DO3
System A
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19. More features
• Decision tree and impact of design decisions
• Design process as a time-based graph
• Statistics per view, component, user
• Domain tailoring for process and views as well as
glossaries, taxonomies, and domain-specific phenomena
• Relationship-based exploration or cause-effect analysis
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20. What the Integration Framework is?
• Be invisible and seamless
• Support the typical activities
SHOULD • Provide help
• Restrict process choice
• Restrict tool choice
SHOULD • Restrict formalism choice
NOT
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21. Summary
• Strengths: “Making the implicit explicit  bridging the gap”
– Know the exact implication of each design decision
– Reuse models (resume from previous design steps, do not start from
the scratch)
– Continuous integration at model/design level (not only during
realization)
– Keep dependencies in control
• Dealing with heterogeneous models
• Continuous conflict detection
– Better / easier communication within design team
• Weaknesses:
– Too generic approach (does not support concrete methods and tools)
– Requires discipline and introduces overhead
– Introduces other way of working
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22. Modeling: the holy grail for designing complex
systems!
flow
view
model
What did we miss?
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23. Thank you for your attention!
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