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From Comparison Matrix to
Variability Model
The Wikipedia Case Study
Presented at Automated Software Engineering (ASE’13) conference
Product
Author

First Name

Last Name

Age

Nat.

Ph.D.?

Posit.

Affil.

Spoken
Lang

Nicolas

Sannier

32

French

soon

PhD Student,
Future
Postdoc?

Inria

French,
English,
Reunion
Isl. creole

Mathieu

Acher

29

French

Yes

Associate
Prof.

University
of Rennes
1, Inria,
IRISA

French,
English

Benoit

Baudry

-

French

Yes

Research
Scientist,
Head of
Triskell team

Inria

French,
English
Product Comparison Matrix (PCM)

Product
Author

First Name

Last Name

Age

Nat.

Ph.D.?

Posit.

Affil.

Spoken
Lang

Nicolas

Sannier

32

French

soon

PhD Student,
Future
Postdoc?

Inria

French,
English,
Reunion
Isl. creole

Delayed with a cancelled plane
Mathieu

Acher

29

French

Yes

Associate
Prof.

University
of Rennes
1, Inria,
IRISA

French,
English

Benoit

Baudry

-

French

Yes

Research
Scientist,
Head of
Triskell team

Inria

French,
English

Not available

Compare and Choose your Product Speaker
ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

-3
ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

-4
#1 This is a Product Comparison Matrix (PCM)

ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

-5
#2 This is a Product Comparison Matrix (PCM)

ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

-6
#3 This is a Product Comparison Matrix (PCM)

ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

-7
Promises of Product Comparison Matrices (PCMs)
+ Intuitive and easy to
understand
+ Convenient for
comparing, input for
configuring
+ Rich source of
information and
knowledge

ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

-8
Issues and Challenges
Product Comparison Matrices (PCMs)

- Heterogeneous information
- As the PCM grows up
“more is less”
- Lack of Formalization
- No Automated Support
- Guidance capabilities

- Ad-hoc PCMs

ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

-9
Issues and Challenges
Product Comparison Matrices (PCMs)

- Heterogeneous information
- As the PCM grows up
“more is less”
- Lack of Formalization
- No Automated Support
- Guidance capabilities

- Ad-hoc PCMs

ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

- 10
Understanding PCMs
RQ1 What kind information
is presented in PCMs?
Syntax?
Semantics?
Variability patterns?

RQ2 What is the gap between PCMs
and Variability Models?
Related work
•  Extensive work on spreadsheets
• 

• 

But PCMs are specific spreadsheets

Reverse engineering variability models
• 

Other artefacts (She et al. ICSE’11, Czarnecki et al. SPLC’07, Abbas et al. CSMR’14)

• 

Boolean PCMs (Haslinger et al. FASE’13, Davril et al. FSE’13)
ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

- 11
The Wikipedia case study
•  Open community
•  One of the most important analyzable repository of PCMs
•  300+ PCMs

•  Multiple domains, multiple concerns, large PCMs

ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

- 12
Research Methodology

•  #0 Extraction of all
381 Wikipedia pages
entitled “Comparison of …”
•  #1 A preliminary analysis of some PCMs (variability patterns
definition)
•  #2 A Qualitative analysis of randomly selected 50 PCMs
•  #3 A Quantitative analysis of all extracted Wikipedia PCMs
ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

- 13
Qualitative Analysis: 8 Variability Patterns

1.  Boolean yes/no answers
2.  Partial/constrained yes/no answers
3.  Single-value answers
4.  Multiple values answers
5.  “Unknown” answers
6.  Empty cells
7.  Inconsistent cells
8.  Additional / Extra information

ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

- 14
Automatically Analysis of 300+ Wikipedia PCMs

ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

- 15
Variability Patterns: Quantitative Results
Information type

2

3

4

5

6

7

8

Qualitative analysis

47.29%

3.71%

22.75%

4.37%

10.86%

4.83%

0.55%

5.64%

Quantitative analysis

• 

1

49.4 %

0.8%

20.4%

15.1%

7.5%

6.8%

-

-

Results
•  75-80% of the PCMs content is
manageable as usual by variability constructs
•  20-25% remaining represent uncertainty or
numerical values
•  Calls for more research for modeling and
reasoning about variability

ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

1.  Boolean yes/no answers
2.  Partial/constrained yes/no
answers
3.  Single-value answers
4.  Multiple values answers
5.  “Unknown” answers
6.  Empty cells
7.  Inconsistent cells
8.  Additional / Extra information

- 16
Research Directions
Bridging the Gap
between Product Comparison Matrices (PCMs) and Variability Models (VMs)

Contributors (writers)
No more ad-hoc PCMs
PCMs should be easier to create
and maintain
Hopefully a non intrusive solution,
interoperable with Wikipedia

End users (readers)
Manageable information
Better readability
Better services

Developers (readers and writers)
Enabling analysis tools of PCMs
(e.g., synthesis of variability models)

Long term, more global vision:
Generating product comparators and configurators from variability models and PCMs
Note: VMs act as a formal representation of PCMs and intermediates before devising configurators/comparators/*
VMs are not an end-user solution to visualize the PCM
ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

- 17
Compare and Choose your Answerer!
PCM-driven of course
Look at the Author Comparison Matrix and Choose

Ask your questions ;-)
Product
Author

First Name

Last Name

Age

Nat.

Ph.D.?

Posit.

Affil.

Spoken
Lang

Nicolas

Sannier

32

French

soon

PhD Student,
Future
Postdoc?

Inria

French,
English,
Reunion
Isl. creole

Delayed with a cancelled plane
Mathieu

Acher

29

French

Yes

Associate
Prof.

University
of Rennes
1, Inria,
IRISA

French,
English

Benoit

Baudry

-

French

Yes

Research
Scientist,
Head of
Triskell team

Inria

French,
English

Not available
ASE'2013 - Sannier, Acher and Baudry - From PCM to VM.

- 18

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From PCM to Variability Model: The Wikipedia Case Study

  • 1. From Comparison Matrix to Variability Model The Wikipedia Case Study Presented at Automated Software Engineering (ASE’13) conference Product Author First Name Last Name Age Nat. Ph.D.? Posit. Affil. Spoken Lang Nicolas Sannier 32 French soon PhD Student, Future Postdoc? Inria French, English, Reunion Isl. creole Mathieu Acher 29 French Yes Associate Prof. University of Rennes 1, Inria, IRISA French, English Benoit Baudry - French Yes Research Scientist, Head of Triskell team Inria French, English
  • 2. Product Comparison Matrix (PCM) Product Author First Name Last Name Age Nat. Ph.D.? Posit. Affil. Spoken Lang Nicolas Sannier 32 French soon PhD Student, Future Postdoc? Inria French, English, Reunion Isl. creole Delayed with a cancelled plane Mathieu Acher 29 French Yes Associate Prof. University of Rennes 1, Inria, IRISA French, English Benoit Baudry - French Yes Research Scientist, Head of Triskell team Inria French, English Not available Compare and Choose your Product Speaker
  • 3. ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. -3
  • 4. ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. -4
  • 5. #1 This is a Product Comparison Matrix (PCM) ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. -5
  • 6. #2 This is a Product Comparison Matrix (PCM) ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. -6
  • 7. #3 This is a Product Comparison Matrix (PCM) ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. -7
  • 8. Promises of Product Comparison Matrices (PCMs) + Intuitive and easy to understand + Convenient for comparing, input for configuring + Rich source of information and knowledge ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. -8
  • 9. Issues and Challenges Product Comparison Matrices (PCMs) - Heterogeneous information - As the PCM grows up “more is less” - Lack of Formalization - No Automated Support - Guidance capabilities - Ad-hoc PCMs ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. -9
  • 10. Issues and Challenges Product Comparison Matrices (PCMs) - Heterogeneous information - As the PCM grows up “more is less” - Lack of Formalization - No Automated Support - Guidance capabilities - Ad-hoc PCMs ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. - 10
  • 11. Understanding PCMs RQ1 What kind information is presented in PCMs? Syntax? Semantics? Variability patterns? RQ2 What is the gap between PCMs and Variability Models? Related work •  Extensive work on spreadsheets •  •  But PCMs are specific spreadsheets Reverse engineering variability models •  Other artefacts (She et al. ICSE’11, Czarnecki et al. SPLC’07, Abbas et al. CSMR’14) •  Boolean PCMs (Haslinger et al. FASE’13, Davril et al. FSE’13) ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. - 11
  • 12. The Wikipedia case study •  Open community •  One of the most important analyzable repository of PCMs •  300+ PCMs •  Multiple domains, multiple concerns, large PCMs ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. - 12
  • 13. Research Methodology •  #0 Extraction of all 381 Wikipedia pages entitled “Comparison of …” •  #1 A preliminary analysis of some PCMs (variability patterns definition) •  #2 A Qualitative analysis of randomly selected 50 PCMs •  #3 A Quantitative analysis of all extracted Wikipedia PCMs ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. - 13
  • 14. Qualitative Analysis: 8 Variability Patterns 1.  Boolean yes/no answers 2.  Partial/constrained yes/no answers 3.  Single-value answers 4.  Multiple values answers 5.  “Unknown” answers 6.  Empty cells 7.  Inconsistent cells 8.  Additional / Extra information ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. - 14
  • 15. Automatically Analysis of 300+ Wikipedia PCMs ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. - 15
  • 16. Variability Patterns: Quantitative Results Information type 2 3 4 5 6 7 8 Qualitative analysis 47.29% 3.71% 22.75% 4.37% 10.86% 4.83% 0.55% 5.64% Quantitative analysis •  1 49.4 % 0.8% 20.4% 15.1% 7.5% 6.8% - - Results •  75-80% of the PCMs content is manageable as usual by variability constructs •  20-25% remaining represent uncertainty or numerical values •  Calls for more research for modeling and reasoning about variability ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. 1.  Boolean yes/no answers 2.  Partial/constrained yes/no answers 3.  Single-value answers 4.  Multiple values answers 5.  “Unknown” answers 6.  Empty cells 7.  Inconsistent cells 8.  Additional / Extra information - 16
  • 17. Research Directions Bridging the Gap between Product Comparison Matrices (PCMs) and Variability Models (VMs) Contributors (writers) No more ad-hoc PCMs PCMs should be easier to create and maintain Hopefully a non intrusive solution, interoperable with Wikipedia End users (readers) Manageable information Better readability Better services Developers (readers and writers) Enabling analysis tools of PCMs (e.g., synthesis of variability models) Long term, more global vision: Generating product comparators and configurators from variability models and PCMs Note: VMs act as a formal representation of PCMs and intermediates before devising configurators/comparators/* VMs are not an end-user solution to visualize the PCM ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. - 17
  • 18. Compare and Choose your Answerer! PCM-driven of course Look at the Author Comparison Matrix and Choose Ask your questions ;-) Product Author First Name Last Name Age Nat. Ph.D.? Posit. Affil. Spoken Lang Nicolas Sannier 32 French soon PhD Student, Future Postdoc? Inria French, English, Reunion Isl. creole Delayed with a cancelled plane Mathieu Acher 29 French Yes Associate Prof. University of Rennes 1, Inria, IRISA French, English Benoit Baudry - French Yes Research Scientist, Head of Triskell team Inria French, English Not available ASE'2013 - Sannier, Acher and Baudry - From PCM to VM. - 18