Endringsdyktige og troverdige systemer
– Modellering av avhengigheter for å evaluere
systemkvalitet
15. jan. 2009
Aida Omerovic
SINTEF IKT/UiO
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Outline
„ Motivation
„ PREDIQT method
„ Practical application of the method
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Background
„ System change is inevitable, due to:
„ Maintainance, system evolution
„ Organisational change
„ New collaboration patterns, functionalities, users, regulations,
standards, technologies…
„ Dynamics of systems/componenets in collaboration with varying QoS
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Objectives
„ Trustworthy architecture over time, inspite of adaptions.
„ Preserve both adaptability and trustworthiness.
„ Reduce the time and risk of enabling and deploying more/additional types
of collaborations.
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Approach
„ Only technical, objective and quantifiable aspects
„ Modeling and simulation
„ Predicting architectural change impacts on relevant
quality characteristics
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PREDIQT:
“Model Based Prediction of Change Impacts
on Architecture Quality”
„ Enables prediction of architectural change-impacts on the quality
characteristics.
„ Prior to change deployment
„ Preventative or adaptive, rather than a corrective approach
„ Based on
„ Quality models
„ Design models
„ Dependency views
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Method overview: the output levels
Dependency views
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Method overview: the process
Usage
profile, SLA,
requirements
Define
requirements
Collect input
Quality
models
Design
models
(UML, ISO)
(UML)
Phase 1: creation and evaluation of the prediction models
Dependency
views (UML)
Phase 2: Use of the models to predict impacts of changes
Change
deployed?
Quality
prediction
Change
within the
predictability
domain?
Quality impact
analysis and
simulation
No
New change
enforcement
on prediction
models
Models QA
Yes
Revise
prediction
models?
Estimation
Statistics
Yes
Measurement
Indicators
Logs
No
Fit the models
(quantitative and
graphical)
Model evaluation:
-Evaluate quality of predictions
-Derive the predictability domain
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Applying the method
A case study addressing
quality prediction of “Validation Authority service” (DNV)
Fall 2008
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Extracts from
VAS specific quality models
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Conceptual VA quality model - overall
Quality: "The totality of characteristics of an entity that bear on its ability
to satisfy stated and implied needs" [ISO 8402]
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Conceptual VA quality model - availability
Def.: “the capability of the software product to be in a state to perform a
required function at a given point in time, under stated conditions of
use.” [ISO/IEC 9126-1]"
Rating: Availability
uptime
uptime + downtime
Have to take into account overall availability, as well as service continuity.
Downtime: incorrect operation time, downtime (planned or unplanned) etc.
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Extracts from design models of
Validation Authority Service
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VA interfaces
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Certificate validation
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Signature verification
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A general dependency view
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Dependency views
„ Based on quality and design models we derive attribute specific
dependency views.
„ Decomposition is carried on until estimates can be assigned with
acceptable certainty.
„ Nodes on the views: modules, subsystems, services and aspects.
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Simulations
•
Dependency views for each quality attribute
•
Sensitivity analysis
•
Tool supported simulation of change impacts
•
On ALL the dependency views, automatically
Next, live demos with an exemplary change
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Fitted dependency views
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Fictitious values
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Sensitivity
1,00
Availability
0,95
0,90
0,85
0,80
0,75
0,70
0,65
0
0,2
0,4
0,6
0,8
1
Updates
Upgrading
Monitoring
Database eff. mech.
Message routing
OS support services
Middleware support serv.
Hardware
Network
Measures for OP env. prot.
User management
Gateway
Other
Current
QCF
Sensitivity
1,00
Availability
0,95
0,90
0,85
0,80
0,75
0,00
0,10
0,20
0,30
EI
0,40
0,50
Updates
Upgrading
Monitoring
Database eff. mech.
Message routing
OS support services
Middleware support serv.
Hardware
Network
Measures for OP env. prot.
User management
Gateway
Other
Current
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Fictitious values
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Fitted dependency views
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Fictitious values
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Sensitivity
Updates
Upgrading
Monitoring
Database eff. mech.
Message routing
OS support services
Middleware support serv.
Hardware
Network
Measures for OP env. prot.
User management
Gateway
Other
Current
Scalability
0,97
0,92
0,87
0,82
0,77
0
0,2
0,4
0,6
0,8
1
QCF
Sensitivity
1,00
Scalability
0,95
0,90
0,85
0,80
0,75
0,00
0,05
0,10
0,15
EI
0,20
0,25
Updates
Upgrading
Monitoring
Database eff. mech.
Message routing
OS support services
Middleware support serv.
Hardware
Network
Measures for OP env. prot.
User management
Gateway
Other
Current
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Fictitious values
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Fictitious values
Sensitivity
1,00
0,95
0,90
0,85
0,80
0,75
0,70
0,65
0,60
0
0,2
0,4
0,6
QCF
0,8
1
Updates
Upgrading
Monitoring
Database eff. mech.
Message routing
OS support services
Middleware support serv.
Hardware
Network
Measures for OP env. prot.
User management
Gateway
Other
Current
Security
Security
Sensitivity
1,00
0,95
0,90
0,85
0,80
0,75
0,70
0,65
0,60
0,00
0,10
0,20
EI
0,30
0,40
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Updates
Upgrading
Monitoring
Database eff. mech.
Message routing
OS support services
Middleware support serv.
Hardware
Network
Measures for OP env. prot.
User management
Gateway
Other
Current
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Fitted dependency views
Sensitivity
Fictitious values
Availability
1,000
Sensitivity
Scalability
Availability
0,800
0,600
Current
0,500
Other
0,400
Scalability
1,00
Security
0,700
Total quality
Total quality
0,900
0,95
Security
0,90
0,85
Other
0,80
Current
0,75
0
0,2
0,4
0,6
Quality attribute
0,8
1
0,00
0,10
0,20
0,30
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Contrib
0,40
0,50
0,60
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Applying PREDIQT
1. Specify the change
2. Enforce the change on the prediction models
„
Design models, nodes (and arcs) of dependency views
3. Establish whether the change is within the prediction domain
„
If point 2 was feasible and sensitivity within the acceptable threshold
4. Simulate the impacts on the dependency views
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Summary
„ The method enables prediction of implications of architectural changes
on the quality characteristics.
„ Applicable as a preventative or adaptive approach at any lifecycle stage
„ Reduces the time and risk of enabling and deploying adaptions
„ Tried out in a major case study and evaluated empirically
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Thank you!
Comments, questions?
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