Towards Multi-view Feature-Based Configuration

Meta modeling

Jorn Moret [ID3510085 – Group 3]J.G.Moret@students.uu.nl

4/10/2013

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Authors Main concepts PDD Example Related literature

Intro

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Arnaud Hubaux (Former Postdoc at University of Namur)

Patrick Heymans(Professor at University of Namur)

Pierre-Yves Schobbens(Professor at University of Namur)

Dirk Deridder (Former postdoc at Vrije Universiteit Brussel )

Authors

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Software product line (SPL) Feature diagram Feature-based configuration (FBC)

Visualize constraints: Extending feature diagrams with multiple

‘views’

Visualizations Greyed Pruned Collapsed

Main concepts

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Software product line (SPL) Feature diagram Feature-based configuration (FBC)

Visualize constraints: Extending feature diagrams with multiple

‘views’

Visualizations Greyed Pruned Collapsed

Main concepts

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Software product line (SPL) Feature diagram Feature-based configuration (FBC)

Visualize constraints: Extending feature diagrams with multiple

‘views’

Visualizations Greyed Pruned Collapsed

Main concepts

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Software product line (SPL) Feature diagram Feature-based configuration (FBC)

Lack of tailoring towards specific concern

Visualize constraints: Extending feature diagrams with multiple

‘views’

Visualizations Greyed Pruned Collapsed

Main concepts

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Software product line (SPL) Feature diagram Feature-based configuration (FBC)

Visualize constraints: Extending feature diagrams with multiple

‘views’

Visualizations Greyed Pruned Collapsed

Main concepts

Manufacturer

Customer

Government

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Software product line (SPL) Feature diagram Feature-based configuration (FBC)

Visualize constraints: Extending feature diagrams with multiple

‘views’

Visualizations Greyed Pruned Collapsed

Main concepts

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PDD

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Example

Decide upon concerns1. Car Manufacturer2. Customer3. Government

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Example

Allocate views1. Car Manufacturer:

Engine, Transmission, Performance, Directives

2. Customer: Gas, Electric, Manual, Automatic, 180Hp, 240Hp

3. Government: Weight, CO2 emission

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ExampleManufacturer

Apply views1. Car Manufacturer:

Engine, Transmission, Performance, Directives

2. Customer: Gas, Electric, Manual, Automatic, 180Hp, 240Hp

3. Government: Weight, CO2 emission

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ExampleManufacturer

Customer

Apply views1. Car Manufacturer:

Engine, Transmission, Performance, Directives

2. Customer: Gas, Electric, Manual, Automatic, 180Hp, 240Hp

3. Government: Weight, CO2 emission

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ExampleManufacturer

Customer

Government

Apply views1. Car Manufacturer:

Engine, Transmission, Performance, Directives

2. Customer: Gas, Electric, Manual, Automatic, 180Hp, 240Hp

3. Government: Weight, CO2 emission

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Example

Check view coverage No overlooked features? Feature not part of a view inferred from

others?

Manufacturer

Customer

Government

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ExampleManufacturer

Customer

Government

Check view interactions Feature selection dependency

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ExampleManufacturer

Customer

Government

Create visualizations:

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ExampleManufacturer

Customer

Government

Decide upon visible features

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Feature modeling First introduced by Kang et al. (1990) FDs origins from SPL Car manufacturers in the 80s

Rosenmüller et al. (2011) Use of seperate FDs for each dimension

Similar method by Zhao et al. (2008) But applied to classic FDs

Related literature

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? Questions