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Automating the Formalization of Product Comparison Matrices

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Automating the Formalization of Product Comparison Matrices

  1. 1. Automating the Formalization of Product Comparison Matrices Guillaume Bécan, Nicolas Sannier, Mathieu Acher, Olivier Barais, Arnaud Blouin, Benoit Baudry
  2. 2. Product lines everywhere Automating the Formalization of Product Comparison Matrices - 2
  3. 3. Product Comparison Matrices (PCMs) Automating the Formalization of Product Comparison Matrices - 3
  4. 4. Services on top of PCMs Automating the Formalization of Product Comparison Matrices - 4 Edit Compare Visualize Filter Rank Merge Configure Multi-objective optimization
  5. 5. Problem Automating the Formalization of Product Comparison Matrices - 5 Edit Compare Visualize … Information is: •Uncontrolled •Heterogeneous •Ambiguous [Sannier et al, ASE 2013] | [[Acer Inc.|Acer]] | [[Acer beTouch E110|beTouch E110]] | {{dts|format=dmy|2010|2|15}} | 1.5 | [[320x240|320x240 QVGA]] | {{convert|2.8|in|mm|abbr=on}} | Touch, accelerometer | * [[GSM]]/​GPRS/​[[Enhanced Data Rates for GSM Evolution|EDGE]] * [[Universal Mobile Telecommunications System|UMTS]] 850 1900 * CSD
  6. 6. Problem Automating the Formalization of Product Comparison Matrices - 6 Common language Transformation Edit Compare Visualize … •How to formalize data contained in natural language PCMs? •How to automate the formalization of PCMs? •What tools and services can be built on top of this formalization?
  7. 7. Contributions Automating the Formalization of Product Comparison Matrices - 7 1.Design of a metamodel for product comparison matrices 2.Automated techniques for formalizing raw data into formalized product comparison matrix model 3.Evaluation on 30,000+ cells from Wikipedia
  8. 8. Metamodeling driven by (lots of) data Automating the Formalization of Product Comparison Matrices - 8 Working on the metamodel since February 2013 300+ PCMs – 300,000 cells Numerous domains Manual review of 50 PCMs (thousands of cells) Statistics on all PCMs Analysis of Wikipedia syntax for tables Automated transformation of all PCMs to PCM models
  9. 9. PCM metamodel Automating the Formalization of Product Comparison Matrices - 9
  10. 10. PCM metamodel Automating the Formalization of Product Comparison Matrices - 10 Structure of a PCM
  11. 11. PCM metamodel Automating the Formalization of Product Comparison Matrices - 11 Feature/Product oriented
  12. 12. Automating the Formalization of Product Comparison Matrices - 12 Formalized interpretation of a cell Data types: Boolean, Integer, Real Special values: Unknown, Empty, Inconsistent, Partial PCM metamodel row string formalized integer
  13. 13. Contributions Automating the Formalization of Product Comparison Matrices - 13 1.Design of a metamodel for product comparison matrices 2.Automated techniques for formalizing raw data into formalized product comparison matrix model 3.Evaluation on 30,000+ cells from Wikipedia
  14. 14. Approach Automating the Formalization of Product Comparison Matrices - 14 Parsing: transform a PCM artefact in a PCM model PCM PCM model parsing preprocessing extracting information exploiting PCM model PCM model PCM metamodel S E R V I C E S | [[Acer Inc.|Acer]] | [[Acer beTouch E110|beTouch E110]] | {{dts|format=dmy|2010|2|15}} | 1.5 | [[320x240|320x240 QVGA]] | {{convert|2.8|in|mm|abbr=on}} | Touch, accelerometer | * [[GSM]]/​GPRS/​[[Enhanced Data Rates for GSM Evolution|EDGE]] * [[Universal Mobile Telecommunications System|UMTS]] 850 1900 * CSD Enable the development of a generic formalization process
  15. 15. Approach Automating the Formalization of Product Comparison Matrices - 15 Preprocessing: Contributors cannot be trusted: missing cells, headers everywhere We have to normalize the matrix and identify headers Default strategy: first line and first column are headers PCM PCM model parsing preprocessing extracting information exploiting PCM model PCM model PCM metamodel S E R V I C E S
  16. 16. Approach Automating the Formalization of Product Comparison Matrices - 16 Extracting information: •Identify features and products •Interpret cells based on a set of syntactic rules (regex) PCM PCM model parsing preprocessing extracting information exploiting PCM model PCM model PCM metamodel S E R V I C E S List of rules: … "d+" => Integer … match Integer(100) Same process as the metamodel for creating the rules
  17. 17. Contributions Automating the Formalization of Product Comparison Matrices - 17 1.Design of a metamodel for product comparison matrices 2.Automated techniques for formalizing raw data into formalized product comparison matrix model 3.Evaluation on 30,000+ cells from Wikipedia
  18. 18. Evaluation Automating the Formalization of Product Comparison Matrices - 18 Experimental settings: •75 PCMs from Wikipedia •Headers specified manually •Automated extraction of information PCM PCM model parsing preprocessing extracting information PCM model PCM model PCM metamodel exploiting S E R V I C E S RQ1 RQ2 RQ3
  19. 19. Evaluation Automating the Formalization of Product Comparison Matrices - 19 Task: check interpretation of each cell (30,000+) •Validate •Correct it with existing concept •Correct it with a new concept •I don’t know / there is no interpretation 20 evaluators Online editor
  20. 20. Evaluation Automating the Formalization of Product Comparison Matrices - 20 Metrics: •Number of valid cells •Number of cells corrected with concepts from the metamodel •Number of cells corrected with new concepts •List of new concepts
  21. 21. Evaluation Automating the Formalization of Product Comparison Matrices - 21 RQ1: To what extent can PCMs be formalized? 93.11% of the cells are valid 2.61% are corrected with concepts from the metamodel 4.28% are invalid and the evaluators proposed a new concept •Dates •Dimensions and units •Versions Solution: •Add corresponding data types to the metamodel •Create new rules for interpreting cells
  22. 22. Evaluation Automating the Formalization of Product Comparison Matrices - 22 RQ2: To what extent can the formalization be automated? 93,11% of the cells are correctly formalized Formalization errors may arise from 4 main areas: •Overlapping concepts (e.g. what does an empty cell mean?) •Missing concepts (e.g. dates, versions…) •Missing interpretation rules •Bad rules
  23. 23. Evaluation Automating the Formalization of Product Comparison Matrices - 23 RQ3: What services can be built on top of formalized PCMs? Editing and formalizing PCMs Warnings during edition (inconsistent cells) Filtering capabilities Translate PCMs to variability models The metamodel provides •Feature/product oriented perspective •Clear semantics
  24. 24. Results of the evaluation Automating the Formalization of Product Comparison Matrices - 24 We now have a common language for PCMs •validated by humans •validated by transformation •validated by the editor A large proportion of the formalization can be automated BUT human is necessary Good news: the editor can help formalizing the data
  25. 25. Future work Automating the Formalization of Product Comparison Matrices - 26 Universal editor Support large datasets Community of PCM contributors Synchronization with Wikipedia
  26. 26. Questions? Automating the Formalization of Product Comparison Matrices - 27 PCM PCM model parsing preprocessing extracting information exploiting PCM model PCM model PCM metamodel S E R V I C E S

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