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Prof. Dr.-Ing. Ina Schaefer (joint work with Mirco Tribastone and Matthias Kowal)Institute of Software Engineering and Automotive Informatics
Technische Universität Braunschweig
Cogenhagen, 18 November 2013
Efficient Performance Analysis for Variant-Rich Systems
18 November 2013 | Ina Schaefer | Efficient Performance Analysis of Variant-Rich Systems| 2
The Problem with Evolution
Scenario Software system with many variants Design-time and/or run-time
Evolution Types Anticipated Changes Unanticipated Changes Runtime Changes
Challenges Analysis of non-functional properties (performance, reliability)? Design-time: optimal configuration (e.g. performance/cost trade-off)? Run-time: SLAs not fulfilled which configuration to choose?
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Project Goals
1. Performance specification and analysis on high level models (e.g., UML)
2. Modeling of variability and evolution at design time and runtime
3. Efficient design time and runtime analysis wrt. quantitative properties
4. Model-based development tool chain for SPS/PLC programming of evolving software families
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Solution Approach
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Design-Level Modeling
T1
T4T3
T2T5
Ma
pp
ing
Co
nsi
ste
ncy
Workflow
Architecture
C1C5
C4C2
C3
C6
Ma
pp
ing
Co
nsi
ste
ncy
Behavioural S1 S2 S3 S4
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Family-based performance analysis
Domain: behavioral models of workflow-type software systems such as Service-oriented architectures Automation systems Data centers … in general, systems where the focus in on the control flow
Why models? To use on-line for prediction/adaptation
What models? UML Activity diagrams with performance annotations
Problem: The analysis of a model with a given set of parameters cannot be reused to analyze the model with another set
Solution: Family-based Symbolic analysis!
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UML activity diagrams
Performance-annotated activity diagrams
Arrival rate of
external jobs Service rate
Probability
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Solution of performance-annotated activity diagrams
Markov chains have infinite state-space. Parametric model checking approaches not possible.
But they can be analyzed with a matrix of size equal to the number of nodes (Jackson network)
Idea: Make this analysis symbolic. One analysis for all possible model variants.
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Delta modeling for variant specification
Variant 1
Core model
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Delta modeling for variant specification (2)
Core model
Variant 2
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Putting it all together: the 150% model
A modified rate
A removed edge
An added edge
A core element
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Symbolic analysis via matrix solution of the 150% model
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Symbolic analysis via matrix solution of the 150% model
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Symbolic vs numerical analysis in practice
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PPU Case Study
Description of 9/15 scenarios as feature model without cardinalities without attributes only significant hardware changes
Modelling 9/15 scenarios as activity diagrams scenario 0 is the delta core 8 scenarios can be achieved using different deltas with additional performance annotations
9/15 scenarios run on real PPU
© by AIS
18 November 2013 | Ina Schaefer | Efficient Performance Analysis of Variant-Rich Systems| 16
Prototypical Tool Chain
File*.uml *.deltaad *.export
PEPADeltaAD
Frame
Control
Import
Add
Export
© by AIS
18 November 2013 | Ina Schaefer | Efficient Performance Analysis of Variant-Rich Systems| 17
Scenario 0
Initial PPU: Stack, Separator, Crane, Slide 90 degree radius Just pick and place process No distinction between workpieces
© by AIS
18 November 2013 | Ina Schaefer | Efficient Performance Analysis of Variant-Rich Systems| 18
Activity Diagram of Scenario 0
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Scenario 3
3rd PPU: Stack, Separator, Crane, Slide, Stamp 180 degree radius Pick, place and stamp process distinction between workpieces (black/white plastic and metal)
© by AIS
18 November 2013 | Ina Schaefer | Efficient Performance Analysis of Variant-Rich Systems| 20
Delta
δ
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Activity Diagram of Scenario 3
Waiting
0.33
CraneToStock ProvideWPWatingForSupplies
WaitingForPickUp
PickUp1
SeparatorRetract
CraneToSlide
PutDownWP1
CraneToStamp
PutDownWP2
Stamp
PickUp2
0.67
10.0
20.0
10.0
1.0
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Conclusion
• Delta Modeling allows modular representation and automatic generation of variant-rich software, here for automation systems.
• Family-based Analysis of Performance is more efficient than product-based analysis for large variant spaces.
• Future Work: Incremental Analysis for Evolving Systems