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Selection and Evolutionary Development of Software-Service
Bundles: a Capability Based Method
Jānis Grabis1, Kurt Sandkuhl21Institute of Information Technology, Riga Technical
University, Kalku 1, Riga, Latvia2 Chair of Business Information Systems , University of Rostock, Albert-Einstein-Straße 22, Rostock, Germany
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Outline
• Motivation• Objectives and problem statement• Method elaboration• Application example• Conclusion
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Software-Service Bundle• Software is
available in different versions
• Software is made available with a number of additional services• Support• Domain expertise• Outsourcing
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State of the Art
• Product-line development– Pohl et al. (2005)
• Packaged software selection– Jadhav and Sonar (2009)
• Evidence based software engineering– Olsson and Bosch (2015)
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CDD Approach
• Assumptions– Suitability of software-service bundles is
context dependent– A bundle optimizing performance is desirable– Clients share software usage data
• Capability driven development (CDD) is an approach for delivering services in different contexts at the desired level of performance– Bērziša et al. (2015)
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Objectives
• To elaborate a method allowing collaboration between vendor and client in selection of the right configuration of software-service bundles and continuous improvement of the selected configuration– Based on the CDD approach
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Problem Statement
Software-service bundle
O1 O2
O3 O4
O5 O6
Performance and context
data
Vendor
Client A
Context
Performance
O5
Client B
Context
Performance
O4
Client C
Context
?
?
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Evolutionary development process
Create capability support matrix
Define capability model
Engage new client
Select appropriate configuration Deploy solution
Monitor delivery
Goals not achievedContext has changed
• Capability model• What factors affect service delivery
and which solutions could be used• Capability support matrix
• Which configuration is suitable in a specific context situation
• Continuous improvement• Development of new configurations
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Evolutionary Development Stages
Design stage
Delivery stage
Evolution
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Design Stage
• Initial configuration of the software-service bundle is selected and deployed for a new client
• Relevant parameter for the selection:– Context elements: have a context range– Context situations: combinations of context
element values from the context range– Most plausible context situation Cnew for a new
client– Configurations Oj derived from
Capability Support Matrix• Client also sets KPI• Least cost configuration Oj appropriate for
context situation faced by the new client
11
1
1 N2 …
1
H
2…
Configurations
Cont
ext S
ituat
ions CSM
),...,( 1 iiTii crcrCR
N
H
CRCRCSCS ...
,...,
1
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ij CSCSaj
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Delivery Stage
• Software-service bundle is in use by the client• Context situations and delivery performance are monitored• Delivery performance:
– Monitoring is based on real-time values of KPI– Actual values are compared to target values– On underperformance, recommendation to revise solution is
issued• Context monitoring
– Comparison of observed context situation with context situations supported by current configuration
– If current configuration no longer fits, warning is issued• Context monitoring serves as an advanced warning system
to potential performance deterioration
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Evolution
• Adjustment of software-service bundle to changing circumstances
• Violations of performance objectives or unsupported context situations suggest an upgrade of the current configuration
• Alternative ways– Selection of a more suitable configuration from
CSM– Reevaluate CSM for the software product– Special software-service bundle needs to be
developed
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Application Example
• Business information exchange process–Manual processing– Automated processing– Outsourcing
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Capability Model
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Capability support matrixProcessing load level
Load volatility O1 O2 O3
Low Low 1 Low Medium 1 1 Low High 1 Medium Low 1 Medium Medium 1 1Medium High 1High Low 1 High Medium 1High High 1
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Simulated Evolution
• Demand for data processing services is simulated– Changing demand level– Changing demand volatility
• EXP1– Is manual processing appropriate for low
demand situation?• EXP2– Is outsourcing needed for high volatility
situations?
low,if 100medium,if 00 1000
high,if 1000 PLC
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Simulation Results (EXP1)
O1 O2
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Simulation Results (EXP2)
O2 O3
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Conclusion
• Incentives for data sharing• Limitations of simulation based
evaluation• Cost of evolutionary development