an analogy to composition filters mehmet aksit ([email protected] ://trese.cs.utwente.nl trese...
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An analogy toComposition Filters
Mehmet Aksit
([email protected] http://trese.cs.utwente.nl
TRESE Group, Department of Computer Science
University of Twente
Postbox 217, 7500 AE
Enschede, The Netherlands
TRESE e-tutorial series 03
2/31© 2001 TRESE Group, University of Twente
trese.cs.utwente.nl
Copyright statement
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If you use part or whole of the material for a non-commercial purpose, then you have to make a reference to our web-site "taken from http://trese.cs.utwente.nl" and always include these two copyright conditions.
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Table of contents
An analogy
References
Filters
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Explain meplease what the
important characteristicsof Composition Filters
are?With pleasure!
I will try to explain you by making ananalogy between Composition Filters
and a real world example.
An analogy to Composition Filters
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Objective: taking a picture
Assume that wewant to take apicture of this
beautiful flower!
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Objective: taking a picture (cont’ed)
This is the camerawhat we have!
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Problem (1): camera cannot focus
This is thepicture we get!
d < min focus
Unfortunatelythe camera
cannotfocus on the
image.The camera is
too close!
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We can builda new dedicatedcamera for this
problem
Sir!Can you build acamera for me
that cantake picturesfrom 2 cm.
A dedicated solution (1)
I am a cameramanufacturer!
$ $
With pleasurewe make a camerafor you, but:$$$$$
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Problem (2): light is not suitable
We solve thefocusing problem!
Lets turn the light on!
Unfortunatelythe light is not
suitable forthe film!
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We can builda new dedicatedcamera for this
lighting!
We neednow a camera
which cantake pictures
with thislighting!
A dedicated solution (2)
No problem!
$ $
With pleasurewe make a camerafor you, but:$$$$$
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Problem (3): not sufficient light intensity
Unfortunately, sometimeswe do not have a
possibility of extra lighting.We must be able to
takea picture in
darkness. Do we needa special camera
which can intensify images?
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Each time a problemis experienced,
a new camera hadto be built.
This is too expensive!
Finding a dedicated solutionfor every problem is not
economical.
We must also be sure that
the solutionsare able to work
together.
Dedicated solutions
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Using modular extensions
May be we should not build adedicated camera each time we
have a new problem!Wait a minute! Why not use
a close up lens as an extension?
I have now a sharp picture. A modular extension is an
economical solution
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Using independent extensions
What if we experience a lightingproblem?
We can use a color filter! We solved the second
problemas well. These extensions
arerather independent from
each other!
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Open ended solutions
If we experience newproblems, such as
image intensification,we may add additional
extensions
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Well-defined semantics
Each extensionmust address a single concern
and have awell-definedsemantics!
extensionsfactory
Our extensionsare certified!
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Run-time solutions
I think there are differentkinds of photographers!Professionals would like
to choose the rightsolution whenever
they need to
“extensions at run-time”
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Compile-time solutions
Amateur photographers, however, may prefer
pre-installed solutions.For them, cameras must be
manufactured at thefactory!
“extensions at compile-time”
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Flexibility in selecting run-time or compile-time solutions
It must be easy toswitch between
run-timeor compile-time
solutions!
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Summary of the solution strategy
Modular extensions;
Independent extensions;
Open-ended solutions;
Well-defined semantics;
Switching between run-time or compile-time solutions.
Let me summarizethe characteristics
of my solution:
Actually, these are alsothe characteristics
of Composition Filters!
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Problems of current OO programs
If the requirementsevolve, current object-oriented programs may
require excessivenumber of
re-definitions.See for exampleour e-tutorial 01
“Evolution problems inObject Oriented Modeling”
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Evolution problems
It looks like that if softwareincorporates non-trivial code,for example, multiple views,
history sensitivity,synchronization, real-time,
constraints, dynamic behavior,it does not evolve easily.
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Filters are modular extensions
Instead of providingdedicated solutions
by modifyingclass descriptions, Composition Filters
offers modular extensions toclass abstractions
expressed in languages likeJava, C++ and Smalltalk.
a filter
A modularextensiona class
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Filters are independent extensions
In case more than one concernhas to be expressed, multiple
filters can be used.
Modular &independentextensions
a class
filter1
filter2
filter3
filter4
Each filter transforms incomingand/or outgoing messages
to/from object.
message
Filters are independent ofeach other!
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Filters are open-ended
New filter types can bedefined by programmers or
may be provided as libraries.However, filter definitions must
be carried out carefully.
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Well-defined semantics
Filters have well-definedsemantics.
For example we havedefined the following filters:
Concern Filter typePre-post conditions ErrorMultiple views ErrorDynamic inheritance DispatchDelegation DispatchLayered architecture MetaHistory sensitivity Meta + history classProtocol Meta + protocol classSynchronization WaitReal time RealTime
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Declarative specifications
Filters are expressed usingdeclarative specifications.
a filter specification
interpreter compiler
run-time solution compile-time solution
Filters can be interpreted,providing run-time solutions,
or they may be compiled,providing faster solutions.
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Monitoring
DynamicMail
LockingMail
These characteristics enhanceobject-oriented programs.
For example, in E-tutorial 01,I presented an evolution
scenario. Classes Email andUSViewMail were extended by
the following classes:
Warning2Mail
ORViewMail
USViewMail
EMailWarning2Mail,
LockingMail,DynamicMail
ORViewMail,
Here the concerns aremultiple views, history
sensitivity, synchronizationand dynamic protocols.
Evolution scenario
& monitoring
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Evolution scenario
To know more about implementation of the scenariousing Composition Filters please refer to:
http://trese.cs.utwente.nl/courses/e_tutorials/evolution_cf.ppt
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References
For more information please refer to:
1. Composition Filters homepage
2. Publications on Composition Filters
2. Implementations of Composition Filters
3. A historical perspective on Composition Filters
4. e-tutorial 01 “Evolution problems in OO modeling”
5. e-tutorial 02 “Solving the evolution problems using Composition Filters”
Do you havereferences?
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More information?
If you want to have moreinformation, just send an email:
Mehmet Aksit: [email protected] Bergmans: [email protected]