Advertisement

Defining and Validating a Multimodel Approach for Product Architecture Derivation and Improvement

  • Javier González-Huerta
  • Emilio Insfrán
  • Silvia Abrahão
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8107)

Abstract

Software architectures are the key to achieving the non-functional requirements (NFRs) in any software project. In software product line (SPL) development, it is crucial to identify whether the NFRs for a specific product can be attained with the built-in architectural variation mechanisms of the product line architecture, or whether additional architectural transformations are required. This paper presents a multimodel approach for quality-driven product architecture derivation and improvement (QuaDAI). A controlled experiment is also presented with the objective of comparing the effectiveness, efficiency, perceived ease of use, intention to use and perceived usefulness with regard to participants using QuaDAI as opposed to the Architecture Tradeoff Analysis Method (ATAM). The results show that QuaDAI is more efficient and perceived as easier to use than ATAM, from the perspective of novice software architecture evaluators. However, the other variables were not found to be statistically significant. Further replications are needed to obtain more conclusive results.

Keywords

Software Product Lines Architectural Patterns Quality Attributes Model Transformations Controlled Experiment 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ali-Babar, M., Lago, P., Van Deursen, A.: Empirical research in software architecture: opportunities, challenges, and approaches. Empirical Software Engineering 16(5), 539–543 (2011)CrossRefGoogle Scholar
  2. 2.
    Ali-Babar, M., Zhu, L., Jeffery, R.: A Framework for Classifying and Comparing Software Architecture Evaluation Methods. In: 15th Australian Software Engineering Conference, Melbourne, Australia, pp. 309–318 (2004)Google Scholar
  3. 3.
    Basili, V.R., Rombach, H.D.: The TAME project: towards improvement-oriented software environments. IEEE Transactions on Software Engineering 14(6), 758–773 (1988)CrossRefGoogle Scholar
  4. 4.
    Barkmeyer, E.J., Feeney, A.B., Denno, P., Flater, D.W., Libes, D.E., Steves, M.P., Wallace, E.K.: Concepts for Automating Systems Integration NISTIR 6928. National Institute of Standards and Technology, U.S. Dept. of Commerce (2003)Google Scholar
  5. 5.
    Bosch, J.: Design and Use of Software Architectures. Adopting and Evolving Product-Line Approach. Addison-Wesley, Harlow (2000)Google Scholar
  6. 6.
    Botterweck, G., O’Brien, L., Thiel, S.: Model-driven derivation of product architectures. In: 22th Int. Conf. on Automated Software Engineering, New York, USA, pp. 469–472 (2007)Google Scholar
  7. 7.
    Buschmann, F., Meunier, R., Rohnert, H., Sommerlad, P., Stal, M.: Pattern-Oriented software architecture, vol. 1: A System of Patterns. Wiley (1996)Google Scholar
  8. 8.
    Cabello, M.E., Ramos, I., Gómez, A., Limón, R.: Baseline-Oriented Modeling: An MDA Approach Based on Software Product Lines for the Expert Systems Development. In: 1st Asia Conference on Intelligent Information and Database Systems, Vietnam (2009)Google Scholar
  9. 9.
    Carifio, J., Perla, R.J.: Ten Common Misunderstandings, Misconceptions, Persistent Myths and Urban Legends about Likert Scales and Likert Response Formats and their Antidotes. Journal of Social Sciences 3(3), 106–116 (2007)CrossRefGoogle Scholar
  10. 10.
    Clements, P., Northrop, L.: Software Product Lines: Practices and Patterns. Addison-Wesley, Boston (2007)Google Scholar
  11. 11.
    Czarnecki, K., Kim, C.H.: Cardinality-based feature modeling and constraints: A progress report. In: Int. Workshop on Software Factories, San Diego-CA (2005)Google Scholar
  12. 12.
    Datorro, J.: Convex Optimization & Euclidean Distance Geometry. Meboo Publishing (2005)Google Scholar
  13. 13.
    Davis, F.D.: Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly 13(3), 319–340 (1989)CrossRefGoogle Scholar
  14. 14.
    Douglass, B.P.: Real-Time Design Patterns: Robust Scalable Architecture for Real-Time Systems. Addison-Wesley, Boston (2002)Google Scholar
  15. 15.
    Feiler, P.H., Gluch, D.P., Hudak, J.: The Architecture Analysis & Design Language (AADL): An Introduction. Tech. Report CMU/SEI-2006-TN-011. SEI, Carnegie Mellon University (2006)Google Scholar
  16. 16.
    Gómez, A., Ramos, I.: Cardinality-based feature modeling and model-driven engineering: Fitting them together. In: 4th Int. Workshop on Variability Modeling of Software Intensive Systems, Linz, Austria (2010)Google Scholar
  17. 17.
    Gonzalez-Huerta, J., Insfran, E., Abrahao, S.: A Multimodel for Integrating Quality Assessment in Model-Driven Engineering. In: 8th International Conference on the Quality of Information and Communications Technology (QUATIC 2012), Lisbon, Portugal, September 3-6 (2012)Google Scholar
  18. 18.
    Gonzalez-Huerta, J., Insfran, E., Abrahao, S., McGregor, J.D.: Non-functional Requirements in Model-Driven Software Product Line Engineering. In: 4th Int. Workshop on Non-functional System Properties in Domain Specific Modeling Languages, Insbruck, Austria (2012)Google Scholar
  19. 19.
    Guana, V., Correal, V.: Variability quality evaluation on component-based software product lines. In: 15th Int. Software Product Line Conference, Munich, Germany, vol. 2, pp. 19.1–19.8 (2011)Google Scholar
  20. 20.
    Insfrán, E., Abrahão, S., González-Huerta, J., McGregor, J.D., Ramos, I.: A Multimodeling Approach for Quality-Driven Architecture Derivation. In: 21st Int. Conf. on Information Systems Development (ISD 2012), Prato, Italy (2012)Google Scholar
  21. 21.
    ISO/IEC 25000:2005, Software Engineering. Software product Quality Requirements and Evaluation SQuaRE (2005)Google Scholar
  22. 22.
    Kazman, R., Klein, M., Clements, P.: ATAM: Method for Architecture Evaluation (CMU/SEI-2000-TR-004, ADA382629). Software Engineering Institute, Carnegie Mellon University, Pittsburgh (2000), http://www.sei.cmu.edu/publications/documents/00.reports/00tr004.html Google Scholar
  23. 23.
    Kim, T., Ko, I., Kang, S., Lee, D.: Extending ATAM to assess product line architecture. In: 8th IEEE Int. Conference on Computer and Information Technology, Sydney, Australia, pp. 790–797 (2008)Google Scholar
  24. 24.
    Kitchenham, B.A., Pfleeger, S.L., Hoaglin, D.C., Rosenber, J.: Preliminary Guidelines for Empirical Research in Software Engineering. IEEE Transactions on Software Engineering 28(8) (2002)Google Scholar
  25. 25.
    Kruchten, P.B.: The Rational Unified Process: An Introduction. Addison-Wesley (1999)Google Scholar
  26. 26.
    Martensson, F.: Software Architecture Quality Evaluation. Approaches in an Industrial Context. Ph. D. thesis, Blekinge Institute of Technology, Karlskrona, Sweden (2006)Google Scholar
  27. 27.
    Maxwell, K.: Applied Statistics for Software Managers. Software Quality Institute Series. Prentice-Hall (2002)Google Scholar
  28. 28.
    Olumofin, F.G., Mišic, V.B.: A holistic architecture assessment method for software product lines. Information and Software Technology 49, 309–323 (2007)CrossRefGoogle Scholar
  29. 29.
    Perovich, D., Rossel, P.O., Bastarrica, M.C.: Feature model to product architectures: Applying MDE to Software Product Lines. In: IEEE/IFIP & European Conference on Software Architecture, Helsinki, Findland, pp. 201–210 (2009)Google Scholar
  30. 30.
    Robertson, S., Robertson, J.: Mastering the requirements process. ACM Press, New York (1999)Google Scholar
  31. 31.
    Roos-Frantz, F., Benavides, D., Ruiz-Cortés, A., Heuer, A., Lauenroth, K.: Quality-aware analysis in product line engineering with the orthogonal variability model. Software Quality Journal (2011), doi:10.1007/s11219-011-9156-5Google Scholar
  32. 32.
    Saaty, T.L.: The Analytical Hierarchical Process. McGraw- Hill, New York (1990)Google Scholar
  33. 33.
    Taher, L., Khatib, H.E., Basha, R.: A framework and QoS matchmaking algorithm for dynamic web services selection. In: 2nd Int. Conference on Innovations in Information Technology, Dubai, UAE (2005)Google Scholar
  34. 34.
    Wohlin, C., Runeson, P., Host, M., Ohlsson, M.C., Regnell, B., Weslen, A.: Experimentation in Software Engineering - An Introduction. Kluwer (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Javier González-Huerta
    • 1
  • Emilio Insfrán
    • 1
  • Silvia Abrahão
    • 1
  1. 1.ISSI Research GroupUniversitat Politècnica de ValènciaValenciaSpain

Personalised recommendations