A Systematic Literature Review of Software Product Line Management Tools

  • Juliana Alves Pereira
  • Kattiana Constantino
  • Eduardo Figueiredo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8919)

Abstract

Software Product Line (SPL) management is a key activity for software product line engineering. The idea behind SPL management is to focus on artifacts that are shared in order to support software reuse and adaptation. Gains are expected in terms of time to market, consistency across products, costs reduction, better flexibility, and better management of change requirements. In this context, there are many available options of SPL variability management tools. This paper presents and discusses the findings from a Systematic Literature Review (SLR) of SPL management tools. Our research method aimed at analyzing the available literature on SPL management tools and the involved experts in the field. This review provides insights (i) to support companies interested to choose a tool for SPL variability management that best fits their needs; (ii) to point out attributes and requirements relevant to those interested in developing new tools; and (iii) to help the improvement of the tools already available. As a direct result of this SLR, we identify gaps, such as the lack of industrial support during product configuration.

Keywords

Systematic Literature Review Software Product Lines Variability Management Tools 

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References

  1. 1.
    Asikainen, T., et al.: Using a Configurator for Modelling and Configuring Software Product Lines based on Feature Models. In: Workshop on Software Variability Management for Product Derivation, Software Product Line Conference (SPLC), pp. 24–35 (2004)Google Scholar
  2. 2.
    A Systematic Literature Review of Software Product Line Management Tools, http://homepages.dcc.ufmg.br/~juliana.pereira/SLR
  3. 3.
    Benavides, D., et al.: Fama: Tooling a Framework for the Automated Analysis of Feature Models. In: 1st International Workshop on Variability Modelling of Software Intensive Systems (VaMoS), pp. 129–134 (2007)Google Scholar
  4. 4.
    Bernardo, M., et al.: Architecting Families of Software Systems with Process Algebras. ACM Transactions on Software Engineering and Methodology 11(4), 386–426 (2002)CrossRefGoogle Scholar
  5. 5.
    Beuche, D., et al.: Variability Management with Feature Models. Journal Science of Computer Programming 53(3), 333–352 (2004)CrossRefMATHMathSciNetGoogle Scholar
  6. 6.
    Bonifácio, R., et al.: Hephaestus: A Tool for Managing SPL Variabilities. In: Brazilian Symposium on Components, Architectures and Reuse Software (SBCARS), pp. 26–34 (2009)Google Scholar
  7. 7.
    Botterweck, G., et al.: A Design of a Configurable Feature Model Configurator. In: 3rd International Workshop on Variability Modelling of Software Intensive Systems (VaMoS), pp. 165–168 (2009)Google Scholar
  8. 8.
    Braga, R., et al.: Odyssey: A Reuse Environment based on Domain Models. In: IEEE Symposium on Application-Specific Systems and Software Engineering and Technology (ASSET), pp. 50–57 (1999)Google Scholar
  9. 9.
    Buhne, S., et al.: Modelling Requirements Variability across Product Lines. In: 13th International Conference on Requirements Engineering (RE), pp. 41–50 (2005)Google Scholar
  10. 10.
    Capilla, R., et al.: An Analysis of Variability Modeling and Management Tools for Product Line Development. In: Software and Service Variability Management Workshop - Concepts, Models, and Tools, pp. 32–47 (2007)Google Scholar
  11. 11.
  12. 12.
    Cawley, C., et al.: Interactive Visualisation to Support Product Configuration in Software Product Lines. In: 2nd International Workshop on Variability Modeling of Software-Intensive Systems (VaMoS), pp. 7–16 (2008)Google Scholar
  13. 13.
    Chen, L., Babar, M.A.: A Systematic Review of Evaluation of Variability Management Approaches in Software Product Lines. Journal Information and Software Technology 53(4), 344–362 (2011)CrossRefGoogle Scholar
  14. 14.
    Cirilo, E., et al.: A product Derivation Tool based on Model-Driven Techniques and Annotations. Journal of Universal Computer Science 14(8), 1344–1367 (2008)Google Scholar
  15. 15.
    Clements, P., Northrop, L.: Software Product Lines: Practices and Patterns. Addison-Wesley (2001)Google Scholar
  16. 16.
    Dehlinger, J., et al.: Decimal and PLFaultCAT: From Product-Line Requirements to Product-Line Member Software Fault Trees. In: 29th International Conference on Software Engineering (ICSE), pp. 49–50 (2007)Google Scholar
  17. 17.
    Dhungana, D., et al.: Decisionking: A Flexible and Extensible Tool for Integrated Variability Modeling. In: 1st International Workshop on Variability Modelling of Software-intensive Systems (VaMoS), pp. 119–128 (2007)Google Scholar
  18. 18.
    Dhungana, D., et al.: The Dopler Meta-Tool for Decision-Oriented Variability Modeling: A Multiple Case Study. Journal Automated Software Engineering 18(1), 77–114 (2011)CrossRefGoogle Scholar
  19. 19.
    Dhungana, D., et al.: Integrating Heterogeneous Variability Modeling Approaches with Invar. In: 7th International Workshop on Variability Modelling of Software-intensive Systems, VaMoS (2013)Google Scholar
  20. 20.
    Djebbi, O., et al.: Industry Survey of Product Lines Management Tools: Requirements, Qualities and Open Issues. In: 15th IEEE International Requirements Engineering Conference (IREC), pp. 301–306 (2007)Google Scholar
  21. 21.
    Eriksson, M., et al.: The Pluss Toolkit: Extending Telelogic Doors and IBM-Rational Rose to Support Product Line Use Case Modeling. In: 20th International Conference on Automated Software Engineering (ASE), pp. 300–304 (2005)Google Scholar
  22. 22.
    Figueiredo, E., et al.: Evolving Software Product Lines with Aspects: An Empirical Study on Design Stability. In: 30th International Conf. on Soft. Eng. (ICSE), pp. 261-270 (2008)Google Scholar
  23. 23.
    Frakes, W.B., et al.: Dare-cots: A Domain Analysis Support tool. In: International Conference of the Chilean Computer Science Society, pp. 73–77 (1997)Google Scholar
  24. 24.
    Gaia, F., et al.: A Quantitative and Qualitative Assessment of Aspectual Feature Modules for Evolving Software Product Lines. In: Science of Computer Programming (SCP), pp. 1–24 (2014)Google Scholar
  25. 25.
    Groher, I., Weinreich, R.: Supporting Variability Management in Architecture Design and Implementation. In: 46th Hawaii International Conference on System Sciences (HICSS), pp. 4995–5004 (2013)Google Scholar
  26. 26.
    Heidenreich, F., et al.: FeatureMapper: Mapping Features to Models. In: International Conference on Software Engineering (ICSE), pp. 943–944 (2008)Google Scholar
  27. 27.
    Hervieu, A., et al.: Pacogen: Automatic Generation of Pairwise Test Configurations from feature models. In: 22nd International Symposium on Software Reliability Engineering (ISSRE), pp. 120–129 (2011)Google Scholar
  28. 28.
    Higgins, J., et al.: Cochrane Handbook for Systematic Reviews of Interventions, vol. 5. Wiley Online Library (2008)Google Scholar
  29. 29.
    Jain, A., Biesiadecki, J.: Yam: A Framework for Rapid Software Development. In: 2nd IEEE International Conference on Space Mission Challenges for Information Technology (SMC-IT), pp. 182–194 (2006)Google Scholar
  30. 30.
    Kang, K., et al.: Feature-Oriented Domain Analysis (FODA) Feasibility Study (1990), http://www.sei.cmu.edu/reports/90tr021.pdf/
  31. 31.
    Kim, K. et al.: Asadal: A Tool System for Co-Development of Software and Test Environment based on Product Line Engineering. In: 28th International Conference on Software Engineering (ICSE), pp. 783–786 (2006) Google Scholar
  32. 32.
    Kitchenham, B., et al.: Systematic Literature Reviews in Software Engineering: A systematic Literature Review. Journal Information and Software Technology 51(1), 7–15 (2009)CrossRefGoogle Scholar
  33. 33.
    Krueger, C.: Biglever Software Gears and the 3-tiered SPL Methodology. In: 22nd Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA), pp. 844–845 (2007)Google Scholar
  34. 34.
    Krut, J.R.W.: Integrating 001 Tool Support in the Feature-Oriented Domain Analysis methodology. Technical Report, Software Engineering Institute (SEI) (1993), http://repository.cmu.edu/cgi/viewcontent.cgi?article=1166&context=sei
  35. 35.
    Laguna, M., Hernández, C.: A Software Product Line Approach for Ecommerce Systems. In: 7th International Conference on e-Business Engineering (ICEBE), pp. 230–235 (2010)Google Scholar
  36. 36.
    Lee, H., et al.: VULCAN: Architecture-Model-Based Workbench for Product Line Engineering. In: 16th International Software Product Line Conference (SPLC), pp. 260–264 (2012)Google Scholar
  37. 37.
    Lisboa, L.B., et al.: A Systematic Review of Domain Analysis Tools. Journal Information and Software Technology 52(1), 1–13 (2010)CrossRefGoogle Scholar
  38. 38.
    Machado, L., et al.: SPLConfig: Product Configuration in Software Product Line. In: Brazilian Congress on Software (CBSoft), Tools Session, pp. 1–8 (2014)Google Scholar
  39. 39.
    Mazo, R., et al.: Variamos: A Tool for Product Line Driven Systems Engineering with a Constraint Based Approach. In: 24th International Conference on Advanced Information Systems Engineering (CAiSE), pp. 1–8 (2012)Google Scholar
  40. 40.
    Mendonça, M. et al.: S.P.L.O.T.: Software Product Lines Online Tools. In: 24th Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA), pp. 761–762 (2009) Google Scholar
  41. 41.
    Myllärniemi, V., et al.: Kumbang tools. In: 11th Software Product Line Conference (SPLC), pp. 135–136 (2007)Google Scholar
  42. 42.
    Park, J., et al.: Dream: Domain Requirement Asset Manager in Product Lines. In: International Symposium on Future Software Technology (ISFST) (2004)Google Scholar
  43. 43.
    Park, K., et al.: An Integrated Software Management Tool for Adopting Software Product Lines. In: 11th International Conference on Computation and Information Science (ICIS), pp. 553–558 (2012)Google Scholar
  44. 44.
    Pereira, J., et al.: Software Variability Management: An Exploratory Study with Two Feature Modeling Tools. In: Brazilian Symposium on Software Components, Architectures and Reuse (SBCARS), vol. 1, pp. 1–10 (2013)Google Scholar
  45. 45.
    Petersen, K., et al.: Systematic Mapping Studies in Software Engineering. In: 12th International Conference on Evaluation and Assessment in Software Engineering (EASE), pp. 68–77 (2008)Google Scholar
  46. 46.
    Pohl, K., et al.: Software Product Line Engineering: Foundations, Principles and Techniques. Springer (2005)Google Scholar
  47. 47.
    Salazar, J.R.: Herramienta para el Modelado y Configuración de Modelos de Características. PhD Thesis, Dpto. Lenguajes y Ciencias de la Comp. Universidad de Málaga (2009)Google Scholar
  48. 48.
    Santos, A., et al.: Test-based SPL Extraction: An Exploratory Study. In: 28th ACM Symposium on Applied Computing (SAC), Software Engineering Track, pp. 1031–1036 (2013)Google Scholar
  49. 49.
    Schmid, K., et al.: Requirements Management for Product Lines: Extending Professional Tools. In: 10th International Software Product Line Conference (SPLC), pp. 113–122 (2006)Google Scholar
  50. 50.
    Sinnema, M., Deelstra, S., Nijhuis, J., Dannenberg, R.B.: COVAMOF: A Framework for Modeling Variability in Software Product Families. In: Nord, R.L. (ed.) SPLC 2004. LNCS, vol. 3154, pp. 197–213. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  51. 51.
    Spinczyk, O., Beuche, D.: Modeling and Building Software Product Lines with Eclipse. In: 19th Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA), pp. 18–19 (2004)Google Scholar
  52. 52.
    SPL Hall of Fame, http://splc.net/fame.html
  53. 53.
    Succi, G., et al.: Holmes: An Intelligent System to Support Software Product Line Development. In: 23rd International Conference on Software Engineering (ICSE), pp. 829–830 (2001)Google Scholar
  54. 54.
    Thao, C., et al.: Software Configuration Management for Product Derivation in Software Product Families. In: 15th International Conference and Workshop on the Engineering of Computer Based Systems (ECBS), pp. 265–274 (2008)Google Scholar
  55. 55.
    Thüm, T., et al.: FeatureIDE: An Extensible Framework for Feature-Oriented Software Development. Journal Science of Computer Programming 79, 70–85 (2014)CrossRefGoogle Scholar
  56. 56.
    Thurimella, A.K., Bruegge, B.: Issue-Based Variability Management Information and Software Technology. Journal Information and Soft. Technology 54(9), 933–950 (2012)CrossRefGoogle Scholar
  57. 57.
    Thurimella, A.K., Janzen, D.: Metadoc Feature Modeler: A Plug-in for IBM Rational Doors. In: International Software Product Line Conference (SPLC), pp. 313–322 (2011)Google Scholar
  58. 58.
    Travassos, G.H., Biolchini, J.: Systematic Review Applied to Software Engineering. In: Brazilian Symposium on Software Engineering (SBES), Tutorials, p. 436 (2007) Google Scholar
  59. 59.
    Unphon, H.: A Comparison of Variability Modeling and Configuration Tools for Product Line Architecture (2008), http://www.itu.dk/people/unphon/technical_notes/CVC_v2008-06-30.pdf
  60. 60.
    Van der Linden, F., et al.: Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering. Springer (2007)Google Scholar
  61. 61.
    Varela, P., et al.: Aspect-Oriented Analysis for Software Product Lines Requirements Engineering. In: Proceedings of the 2011 ACM Symposium on Applied Computing (2011)Google Scholar
  62. 62.
    Varmod-Prime Tool. Software Systems Engineering Research Group/University of Duisburg-Essen, http://paluno.uni-due.de/en/varmod-prime
  63. 63.
    XFeature Modeling Tool, http://www.pnp-software.com/XFeature
  64. 64.
    Wohlin, C. et al.: Experimentation in Software Engineering: An Introduction. Kluwer Academic Publishers (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Juliana Alves Pereira
    • 1
  • Kattiana Constantino
    • 1
  • Eduardo Figueiredo
    • 1
  1. 1.Computer Science DepartmentFederal University of Minas GeraisBelo HorizonteBrazil

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