Skip to main content
SpringerLink
Log in

Recommendation Heuristics for Improving Product Line Configuration Processes

  • Chapter
  • First Online:
Recommendation Systems in Software Engineering

Abstract

In mass customization industries, such as car manufacturing, configurators play an important role both to interact with customers and in engineering processes. This is particularly true when engineers rely on reuse of assets and product line engineering techniques. Theoretically, product line configuration should be guided by the product line model. However, in the industrial context, the configuration of products from product line models is complex and error-prone due to the large number of variables in the models. The configuration activity quickly becomes cumbersome due to the number of decisions needed to get a proper configuration, to the fact that they should be taken in predefined order, or the poor response time of configurators when decisions are not appropriate. This chapter presents a collection of recommendation heuristics to improve the interactivity of product line configuration so as to make it scalable to common engineering situations. We describe the principles, benefits, and the implementation of each heuristic using constraint programming. The application and usability of the heuristics is demonstrated using a case study from the car industry.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    The variability presented here does not necessarily use the same names and expose the same options as online vehicle catalogs.

References

  1. Abbasi, E., Hubaux, A., Heymans, P.: A toolset for feature-based configuration workflows. In: Proceedings of the International Software Product Lines Conference, pp. 65–69, Munich, 22–26 August 2011. doi:10.1109/SPLC.2011.41

    Google Scholar 

  2. Antkiewicz, M., Czarnecki, K.: FeaturePlugin: Feature modeling plug-in for Eclipse. In: Proceedings of the Eclipse Technology eXchange, pp. 67–72, Barcelona, March 2004. doi:10.1145/1066129.1066143

    Google Scholar 

  3. Astesana, J.M., Cosserat, L., Fargier, H.: Constraint-based vehicle configuration: A case study. In: Proceedings of the IEEE International Conference on Tools with Artificial Intelligence, vol. 1, pp. 68–75, Arras, France, 27–29 October 2010. doi:10.1109/ICTAI.2010.19

    Google Scholar 

  4. Batory, D., Benavides, D., Ruiz-Cortés, A.: Automated analysis of feature models: Challenges ahead. Comm. ACM 49(12), 45–47 (2006). doi:10.1145/1183236.1183264

    Article  Google Scholar 

  5. Benavides, D., Trinidad, P., Ruiz-Cortés, A.: Automated reasoning on feature models. In: Proceedings of the International Conference on Advanced Information Systems Engineering, Lecture Notes in Computer Science, vol. 3520, pp. 491–503. Springer, Heidelberg (2005). doi:10.1007/11431855_34

    Google Scholar 

  6. Boussemart, F., Hemery, F., Lecoutre, C., Sais, L.: Boosting systematic search by weighting constraints. In: Proceedings of the European Conference on Artificial Intelligence, pp. 146–150, Valencia, Spain, 22–27 August 2004

    Google Scholar 

  7. Burke, R.: Knowledge-based recommender systems. Encyclopedia of Library and Information Science 69(32), 180–200 (2000)

    Google Scholar 

  8. Clements, P., Northrop, L.M.: Software Product Lines: Practices and Patterns. Addison-Wesley, Reading, MA (2002)

    Google Scholar 

  9. Clements, P., Northrop, L.M.: A framework for software product line practice (2007). URL http://www.sei.cmu.edu/productlines/frame_report/introduction.htm. Version 5.0

  10. van Deursen, A., Klint, P.: Domain-specific language design requires feature descriptions. J. Comput. Inform. Technol. 10(1), 1–17 (2002)

    Article  MATH  Google Scholar 

  11. Dhungana, D., Grünbacher, P., Rabiser, R.: The DOPLER meta-tool for decision-oriented variability modeling: A multiple case study. Int. J. Autom. Software Eng. 18(1), 77–114 (2010). doi:10.1007/s10515-010-0076-6

    Article  Google Scholar 

  12. Diaz, D., Codognet, P.: Design and implementation of the GNU Prolog system. J. Funct. Logic Program. 2001(6), 6:1–6:29 (2001)

    Google Scholar 

  13. Djebbi, O., Salinesi, C.: RED-PL: A method for deriving product requirements from a product line requirements model. In: Proceedings of the International Conference on Advanced Information Systems Engineering, Lecture Notes in Computer Science, vol. 4495, pp. 279–293. Springer, Heidelberg (2007). doi:10.1007/978-3-540-72988-4_20

    Google Scholar 

  14. Dumitrescu, C., Mazo, R., Salinesi, C., Dauron, A.: Bridging the gap between product lines and systems engineering: An experience in variability management for automotive model based systems engineering. In: Proceedings of the International Software Product Lines Conference, pp. 254–263, Tokyo, Japan, 26–30 August 2013a. doi:10.1145/2491627.2491655

    Google Scholar 

  15. Dumitrescu, C., Tessier, P., Salinesi, C., Gérard, S., Dauron, A.: Flexible product line derivation applied to a model based systems engineering process. In: Proceedings of the International Conference on Complex Systems Design & Management, pp. 227–239. Springer, Heidelberg (2013b). doi:10.1007/978-3-642-34404-6_15

    Google Scholar 

  16. Felfernig, A., Jeran, M., Ninaus, G., Reinfrank, F., Reitererand, S., Stettinger, M.: Basic approaches in recommendation systems. In: Robillard, M., Maalej, W., Walker, R.J., Zimmermann, T. (eds.) Recommendation Systems in Software Engineering, Chap. 2. Springer, Heidelberg (2014)

  17. Hadzic, T., Andersen, H.R.: An introduction to solving interactive configuration problems. Tech. Rep. TR-2004-49, The IT University of Copenhagen (2004)

    Google Scholar 

  18. Hadzic, T., Subbarayan, S., Jensen, R.M., Andersen, H.R., Møller, J., Hulgaard, H.: Fast backtrack-free product configuration using a precompiled solution space representation. In: Proceedings of the International Conference on Economic, Technical and Organisational Aspects of Product Configuration Systems, pp. 131–138, Copenhagen, Denmark, 28–29 June 2004

    Google Scholar 

  19. Jiang, Z., Wang, W., Benbasat, I.: Multimedia-based interactive advising technology for online consumer decision support. Commun. ACM 48(9), 92–98 (2005). doi:10.1145/1081992.1081995

    Article  Google Scholar 

  20. Kang, K.C., Cohen, S.G., Hess, J.A., Novak, W.E., Peterson, A.S.: Feature-oriented domain analysis (FODA) feasibility study. Tech. Rep. CMU/SEI-90-TR-21, Carnegie Mellon University, Software Engineering Institute (1990)

    Google Scholar 

  21. Mazo, R., Lopez-Herrejon, R.E., Salinesi, C., Diaz, D., Egyed, A.: Conformance checking with constraint logic programming: The case of feature models. In: Proceedings of the IEEE International Computer Software and Applications Conference, pp. 456–465, Munich, Germany, 18–22 July 2011a. doi:10.1109/COMPSAC.2011.66

    Google Scholar 

  22. Mazo, R., Salinesi, C., Diaz, D.: VariaMos: A tool for product line driven systems engineering with a constraint based approach. In: Proceedings of the CAiSE Forum, CEUR Workshop Proceedings, vol. 855, pp. 147–154, Gdansk, Poland, 28 June 2012a

    Google Scholar 

  23. Mazo, R., Salinesi, C., Diaz, D., Djebbi, O., Lora-Michiels, A.: Constraints: The heart of domain and application engineering in the product lines engineering strategy. Int. J. Inform. Syst. Model. Des. 3(2), 33–68 (2012b). doi:10.4018/jismd.2012040102

    Article  Google Scholar 

  24. Mazo, R., Salinesi, C., Diaz, D., Lora-Michiels, A.: Transforming attribute and clone-enabled feature models into constraint programs over finite domains. In: Proceedings of the International Conference on Evaluating Novel Approaches to Software Engineering, pp. 188–199, Beijing, China, 8–11 June 2011b

    Google Scholar 

  25. Mendonca, M., Wasowski, A., Czarnecki, K.: SAT-based analysis of feature models is easy. In: Proceedings of the International Software Product Lines Conference, pp. 231–240, San Francisco, CA, USA, 24–28 August 2009

    Google Scholar 

  26. Payne, J.W., Bettman, J.R., Johnson, E.J.: The Adaptive Decision Maker. Cambridge University Press, Cambridge (1993)

    Book  Google Scholar 

  27. Pohl, K., Böckle, G., van der Linden, F.J.: Software Product Line Engineering: Foundations, Principles and Techniques. Springer, Heidelberg (2005). doi:10.1007/3-540-28901-1

    Google Scholar 

  28. Salinesi, C., Mazo, R., Diaz, D., Djebbi, O.: Using integer constraint solving in reuse based requirements engineering. In: Proceedings of the IEEE International Requirements Engineering Conference, pp. 243–251, Sydney, NSW, Australia, 27 September–1 October 2010. doi:10.1109/RE.2010.36

    Google Scholar 

  29. Schneeweiss, D., Hofstedt, P.: FdConfig: A constraint-based interactive product configurator. Tech. Rep. arXiv:1108.5586 (2011)

    Google Scholar 

  30. Subbarayan, S.: Integrating CSP decomposition techniques and BDDs for compiling configuration problems. In: Proceedings of the International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, Lecture Notes in Computer Science, vol. 3524. Springer, Heidelberg (2005). doi:10.1007/11493853_26

    Google Scholar 

  31. Subbarayan, S., Jensen, R.M., Hadzic, T., Andersen, H.R., Hulgaard, H., Møller, J.: Comparing two implementations of a complete and backtrack-free interactive configurator. In: Proceedings of the Workshop on CSP Techniques with Immediate Application, pp. 97–111, Toronto, Canada, 27 September 2004

    Google Scholar 

  32. Thompson, C.A., Göker, M.H., Langley, P.: A personalized system for conversational recommendations. J. Artif. Intell. Res. 21(1), 393–428 (2004)

    Google Scholar 

  33. Van Hentenryck, P.: Constraint Satisfaction in Logic Programming. MIT Press, Boston, MA (1989)

    Google Scholar 

  34. von Winterfeldt, D., Edwards, W.: Decision Analysis and Behavioral Research. Cambridge University Press, New York (1986)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Université Paris 1 Panthéon-Sorbonne, Paris, France

    Raúl Mazo, Cosmin Dumitrescu, Camille Salinesi & Daniel Diaz

Authors
  1. Raúl Mazo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cosmin Dumitrescu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Camille Salinesi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Daniel Diaz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Raúl Mazo .

Editor information

Editors and Affiliations

  1. McGill University, Montréal, Québec, Canada

    Martin P. Robillard

  2. University of Hamburg, Hamburg, Germany

    Walid Maalej

  3. University of Calgary, Calgary, Alberta, Canada

    Robert J. Walker

  4. Microsoft Research, Redmond, Washington, USA

    Thomas Zimmermann

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Mazo, R., Dumitrescu, C., Salinesi, C., Diaz, D. (2014). Recommendation Heuristics for Improving Product Line Configuration Processes. In: Robillard, M., Maalej, W., Walker, R., Zimmermann, T. (eds) Recommendation Systems in Software Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45135-5_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-45135-5_19

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-45134-8

  • Online ISBN: 978-3-642-45135-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation