Skip to main content
Log in

Analysis of variability models: a systematic literature review

  • Regular Paper
  • Published:
Software and Systems Modeling Aims and scope Submit manuscript

Abstract

Dealing with variability, during Software Product Line Engineering (SPLE), means trying to allow software engineers to develop a set of similar applications based on a manageable range of variable functionalities according to expert users’ needs. Particularly, variability management (VM) is an activity that allows flexibility and a high level of reuse during software development. In the last years, we have witnessed a proliferation of methods, techniques and supporting tools for VM in general, and for its analysis in particular. More precisely, a specific field has emerged, named (automated) variability analysis, focusing on verifying variability models across the SPLE’s phases. In this paper, we introduce a systematic literature review of existing proposals (as primary studies) focused on analyzing variability models. We define a classification framework, which is composed of 20 sub-characteristics addressing general aspects, such as scope and validation, as well as model-specific aspects, such as variability primitives, reasoner type. The framework allows to look at the analysis of variability models during its whole life cycle—from design to derivation—according to the activities involved during an SPL development. Also, the framework helps us answer three research questions defined for showing the state of the art and drawing challenges for the near future. Among the more interesting challenges, we can highlight the needs of more applications in industry, the existence of more mature tools, and the needs of providing more semantics in the way of variability primitives for identifying inconsistencies in the models.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

Notes

  1. A prominent or distinctive user-visible aspect, quality, or characteristic of a software system or systems [36].

  2. The ability to perform a task or function.

  3. In this paper, proposal and primary study will be used with the same meaning, which is defined in Sect. 9

  4. Testing here is understood as an analysis technique that needs to execute the program to analyze a given property.

  5. http://fosd.net/spl-strategies/.

  6. http://dl.acm.org/.

  7. http://ieeexplore.ieee.org/.

  8. http://www.sciencedirect.com/.

  9. https://scholar.google.com.ar/.

  10. https://www.scopus.com/.

  11. https://link.springer.com/.

  12. http://vamos2014.unice.fr/.

  13. http://splc.net/

  14. We also checked whether these papers were included in the selected libraries as well.

  15. We use the name of the supporting tool provided by the study, when it is specified. Otherwise, we use the surname of the first author.

  16. https://www.eclipse.org/.

  17. https://www.eclipse.org/modeling/emf/.

  18. https://www-01.ibm.com/software/rational/announce.

  19. www.sat4j.org/.

  20. www.choco-solver.org.

  21. https://franz.com/agraph/racer/.

  22. http://zotonic.com/.

  23. http://www.isa.us.es/fama/?BeTTy_Framework.

  24. https://www.ibm.com/support/knowledgecenter/en/SSYQBZ/doors_family_welcome.html.

  25. Percentages do not add up to 100 due to some studies belong to more than one classification.

  26. This figure was made by assuming that when a study use a language, this language support the scenarios indicated in Table 10 for that study.

  27. www.sei.cmu.edu/productlines/.

  28. ISO/IEC 26550:2013 Software and systems engineering—Reference model for product line engineering and management.

References

  1. Abele, A., Lönn, H., Reiser, M., Weber, M., Glathe, H.: Epm: a prototype tool for variability management in component hierarchies. In: Proceedings of the 16th International Software Product Line Conference, vol. 2, SPLC’12, pp. 246–249. ACM, New York(2012)

  2. Abele, A., Papadopoulos, Y., Servat, D., Törngren, M., Weber, M.: The cvm framework—a prototype tool for compositional variability management. In: Benavides, D., Batory, D.S., Grünbacher, P. (eds.) Proceeding of Variability Modelling of Software-Intensive Systems (VAMOS), vol. 37 of ICB-Research Report, pp. 101–105. Universität Duisburg-Essen (2010)

  3. Acher, M., Collet, P., Lahire, P., France, R.B.: Familiar: a domain-specific language for large scale management of feature models. Sci. Comput. Program. 78(6), 657–681 (2013)

    Article  Google Scholar 

  4. Afriyanti, I., Falakh, F.M., Azurat, A., Takwa, B.: Feature model-to-ontology for SPL application realisation (2017). CoRR, arXiv:1707.02511

  5. Aleixo, F.A., Kulesza, U., Oliveira-Junior, E.A.: Modeling variabilities from software process lines with compositional and annotative techniques: a quantitative study. In: Heidrich, J., Oivo, M., Jedlitschka, A., Baldassarre, M.T. (eds.) Product-Focused Software Process Improvement, pp. 153–168. Springer, Berlin (2013)

    Chapter  Google Scholar 

  6. Ampatzoglou, A., Bibi, S., Avgeriou, P., Verbeek, M., Chatzigeorgiou, A.: Identifying, categorizing and mitigating threats to validity in software engineering secondary studies. Inf. Softw. Technol. 106, 201–230 (2019)

    Article  Google Scholar 

  7. Asadi, M., Gröner, G., Mohabbati, B., Gašević, D.: Goal-oriented modeling and verification of feature-oriented product lines. Softw. Syst. Model. 15(1), 257–279 (2016)

    Article  Google Scholar 

  8. Bak, K., Diskin, Z., Antkiewicz, M., Czarnecki, K., Wkasowski, A.: Clafer: unifying class and feature modeling. Softw. Syst. Model. 15(3), 811–845 (2016)

    Article  Google Scholar 

  9. Bashroush, R., Garba, M., Rabiser, R., Groher, I., Botterweck, G.: Case tool support for variability management in software product lines. ACM Comput. Surv. 50(1), 14:1–14:45 (2017)

    Article  Google Scholar 

  10. Benavides, D., Segura, S., Ruiz-Cortés, A.: Automated analysis of feature models 20 years later: a literature review. Inf. Syst. 35(6), 615–636 (2010)

    Article  Google Scholar 

  11. Berger, T., Rublack, R., Nair, D., Atlee, J.M., Becker, M., Czarnecki, K., Wasowski, A.: A survey of variability modeling in industrial practice. In: Proceedings of the 7th International Workshop on Variability Modelling of Software-intensive Systems, VaMoS’13, pp. 7:1–7:8. ACM, New York (2013)

  12. Beuche, D.: Pure::Variants, pp. 173–182. Springer, Berlin (2013)

    Google Scholar 

  13. Bhushan, M., Goel, S., Kaur, K.: Analyzing inconsistencies in software product lines using an ontological rule-based approach. J. Syst. Softw. 137, 605–617 (2018)

    Article  Google Scholar 

  14. Bosch, J.: Design and Use of Software Architectures: Adopting and Evolving a Product-Line Approach. ACM Press/Addison-Wesley Publishing Co., New York (2000)

    Google Scholar 

  15. Braun, G.A., Pol’la, M., Cecchi, L.A., Buccella, A., Fillottrani, P.R., Cechich, A.: A DL semantics for reasoning over ovm-based variability models. In: Proceedings of the 30th International Workshop on Description Logics, Montpellier, France, July 18–21 (2017)

  16. Brereton, P., Kitchenham, B.A., Budgen, D., Turner, M., Khalil, M.: Lessons from applying the systematic literature review process within the software engineering domain. J. Syst. Softw. 80(4), 571–583 (2007). Software Performance

    Article  Google Scholar 

  17. Buccella, A., Cechich, A., Arias, M., Pol’la, M., Doldan, S., Morsan, E.: Towards systematic software reuse of GIS: insights from a case study. Comput. Geosci. 54, 9–20 (2013)

    Article  Google Scholar 

  18. Das, N.C., Ripon, S., Hossain, O., Uddin, M.S.: Requirement analysis of product line based semantic web services. Lect. Not. Softw. Eng. 2, 210–217 (2014)

    Article  Google Scholar 

  19. Causevic, A., Sundmark, D., Punnekkat, S.: Factors limiting industrial adoption of test driven development: a systematic review. In: 4th IEEE International Conference on Software Testing, Verification and Validation, pp. 337–346 (2011)

  20. Chen, L., Ali Babar, M., Ali, N.: Variability management in software product lines: a systematic review. In: Proceedings of the 13th International Software Product Line Conference, SPLC’09, pp. 81–90. Carnegie Mellon University, Pittsburgh (2009)

  21. Chen, L., Ali Babar, M.: A systematic review of evaluation of variability management approaches in software product lines. Inf. Softw. Technol. 53(4), 344–362 (2011)

    Article  Google Scholar 

  22. Classen, A., Boucher, Q., Heymans, P.: A text-based approach to feature modelling: syntax and semantics of tvl. Sci. Comput. Program. 76, 1130–1143 (2011)

    Article  Google Scholar 

  23. Dhungana, D., Tang, C., Weidenbach, C., Wischnewski, P.: Automated verification of interactive rule-based configuration systems. In: Proceedings of the 28th IEEE/ACM International Conference on Automated Software Engineering, ASE’13, pp. 551–561. IEEE Press, Piscataway (2013)

  24. Djebbi, O., Salinesi, C.: Red-pl, a method for deriving product requirements from a product line requirements model. In: Krogstie, J., Opdahl, A., Sindre, G. (eds.) Advanced Information Systems Engineering, pp. 279–293. Springer, Berlin (2007)

    Chapter  Google Scholar 

  25. Durán, A., Benavides, D., Segura, S., Trinidad, P.P., Ruiz-Cortés, A.: Flame: a formal framework for the automated analysis of software product lines validated by automated specification testing. Softw. Syst. Model. 16(4), 1049–1082 (2017)

    Article  Google Scholar 

  26. Eichelberger, H., Schmid, K.: A systematic analysis of textual variability modeling languages. In: Proceedings of the 17th International Software Product Line Conference, SPLC’13, pp. 12–21. ACM, New York (2013)

  27. El Dammagh, M., De Troyer, O.: Feature modeling tools: evaluation and lessons learned. In: De Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds.) Advances in Conceptual Modeling. Recent Developments and New Directions, Volume 6999 of Lecture Notes in Computer Science, pp. 120–129. Springer, Berlin (2011)

  28. Elfaki, A.O.: A rule-based approach to detect and prevent inconsistency in the domain-engineering process. Expert Syst. J. Knowl. Eng. 33(1), 3–13 (2016)

    Article  Google Scholar 

  29. Galster, M., Weyns, D., Tofan, D., Michalik, B., Avgeriou, P.: Variability in software systems 2014; a systematic literature review. IEEE Trans. Softw. Eng. 40(3), 282–306 (2014)

    Article  Google Scholar 

  30. Groher, I., Krueger, C.W., Schwanninger, C.: A tool-based approach to managing crosscutting feature implementations. In: Proceeding of 7th International Conference on Aspect-Oriented Software Development (Industry Track), AOSD, Brussels, Belgium (2008)

  31. Guedes, G., Silva, C., Soares, M., Castro, J.: Variability management in dynamic software product lines: a systematic mapping. In: 2015 IX Brazilian Symposium on Components, Architectures and Reuse Software, pp. 90–99 (2015)

  32. Heidenreich, F., Kopcsek, J., Wende, C.: Featuremapper: Mapping features to models. In: Companion of the 30th International Conference on Software Engineering, ICSE Companion’08, pp. 943–944. ACM, New York (2008)

  33. Horcas, J.-M., Pinto, M., Fuentes, L.: Software product line engineering: a practical experience. In: Proceedings of the 23rd International Systems and Software Product Line Conference—Volume A, SPLC 19, pp. 164–176. Association for Computing Machinery, New York (2019)

  34. Jackson, D.: Software Abstractions: Logic, Language, and Analysis. The MIT Press, Cambridge (2006)

    Google Scholar 

  35. Jalali, S., Wohlin, C.: Systematic literature studies: database searches vs. backward snowballing. In: Proceedings of the 2012 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, pp. 29–38 (2012)

  36. Kang, K., Cohen, S., Hess, J., Nowak, W., Peterson, S.: Feature-oriented domain analysis (FODA) feasibility study. Technical Report CMU/SEI-90-TR-21, Software Engineering Institute, Carnegie Mellon University Pittsburgh, PA (1990)

  37. Karataş, A.S., Oğuztüzün, H., Doğru, A.: From extended feature models to constraint logic programming. Science of Computer Programming, 78(12):2295–2312, (2013). Special Section on International Software Product Line Conference 2010 and Fundamentals of Software Engineering (selected papers of FSEN 2011)

  38. Kitchenham, B., Charters, S.: Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007-001, Keele University and Durham University Joint Report (2007)

  39. Kitchenham, B.: Procedures for performing systematic reviews. Technical Report TR/SE-0401, Keele University, Department of Computer Science, Keele University, UK (2004)

  40. Kitchenham, B., Pearl Brereton, O., Budgen, D., Turner, M., Bailey, J., Linkman, S.: Systematic literature reviews in software engineering—a systematic literature review. Inf. Softw. Technol. 51(1), 7–15 (2009). (Special Section—Most Cited Articles in 2002 and Regular Research Papers)

    Article  Google Scholar 

  41. Kowal, M., Ananieva, S., Thüm, T.: Explaining anomalies in feature models. SIGPLAN Not. 52(3), 132–143 (2016)

    Article  Google Scholar 

  42. Krieter, S., Pinnecke, M., Krüger, J., Sprey, J., Sontag, C., Thüm, T., Leich, T., Saake, G.: Featureide: Empowering third-party developers. In: Proceedings of the 21st International Systems and Software Product Line Conference, vol. B, SPLC’17, pp. 42–45, New York, NY, USA (2017). ACM

  43. Langermeier, M., Rosina, P., Oberkampf, H., Driessen, T., Bauer, B.: Management of variability in modular ontology development. In: Lomuscio, A., Nepal, S., Patrizi, F., Benatallah, B., Brandić, I. (eds.) Service-Oriented Computing—ICSOC Workshops, pp. 225–239. Springer International Publishing, Cham (2014)

  44. Lesta, U., Schaefer, I., Winkelmann, T.: Detecting and explaining conflicts in attributed feature model. In: Proceedings FMSPLE 2015 (2015). arXiv:1504.03014

  45. Lisboa, L.B., Garcia, V.C., Lucrédio, D., Almeida, E.S., Meira, S.R.D.L., Fortes, R.P.M.: A systematic review of domain analysis tools. Inf. Softw. Technol. 52(1), 1–13 (2010)

    Article  Google Scholar 

  46. Lützenberger, M., Küster, T., Konnerth, T., Thiele, A., Masuch, N., Heßler, A., Keiser, J., Burkhardt, M., Kaiser, S., Tonn, J., Kaisers, M., Albayrak, S.: A multi-agent approach to professional software engineering. In: Cossentino, M., El Fallah Seghrouchni, A., Winikoff, M. (eds.) Engineering Multi-Agent Systems, pp. 156–175. Springer, Berlin (2013)

  47. Mauro, J., Nieke, M., Seidl, C., Yu, I.C.: Anomaly detection and explanation in context-aware software product lines. In: Proceedings of the 21st International Systems and Software Product Line Conference—Volume B, SPLC’17, pp. 18–21. ACM, New York (2017)

  48. Mazo, R., Muñoz-Fernández, J.C., Rincón, L., Salinesi, C., Tamura, G.: Variamos: an extensible tool for engineering (dynamic) product lines. In: Proceedings of the 19th International Conference on Software Product Line, SPLC 2015, Nashville, TN, USA, July 20–24, 2015, pp. 374–379 (2015)

  49. Meinicke, J., Thüm, T., Schröter, R., Benduhn, F., Saake, G.: An overview on analysis tools for software product lines. In: Proceedings of the 18th International Software Product Line Conference: Companion Volume for Workshops, Demonstrations and Tools—Volume 2, SPLC’14, pp. 94–101. ACM, New York (2014)

  50. Mendonca, M., Branco, M., Cowan, D.: S.p.l.o.t.: Software product lines online tools. In: Proceedings of the 24th ACM SIGPLAN Conference Companion on Object Oriented Programming Systems Languages and Applications, OOPSLA’09, pp. 761–762. ACM, New York (2009)

  51. Metzger, A., Pohl, K., Heymans, P., Schobbens, P.Y., Saval, G.: Disambiguating the documentation of variability in software product lines: a separation of concerns, formalization and automated analysis. In: 15th IEEE International Requirements Engineering Conference (RE 2007), pp. 243–253 (2007)

  52. Nakajima, S.: Semi-automated diagnosis of foda feature diagram. In: Proceedings of the 2010 ACM Symposium on Applied Computing, SAC’10, pp. 2191–2197. ACM, New York (2010)

  53. Noorian, M., Ensan, A., Bagheri, E., Boley, H., Biletskiy, Y.: Feature model debugging based on description logic reasoning. In: Conference on Distributed Multimedia Systems, pp. 158–164. Knowledge Systems Institute (2011)

  54. Park, K., Ryu, D., Baik, J.: An integrated software management tool for adopting software product lines. In: IEEE/ACIS 11th International Conference on Computer and Information Science, pp. 553–558 (2012)

  55. Pereira, J.A., Constantino, K., Figueiredo, E.: A Systematic Literature Review of Software Product Line Management Tools, pp. 73–89. Springer International Publishing, Cham (2014)

    Google Scholar 

  56. Pereira, J.A., Souza, C., Figueiredo, E., Abilio, R., Vale, G., Costa, H.A.X.: Software variability management: an exploratory study with two feature modeling tools. In: 2013 VII Brazilian Symposium on Software Components, Architectures and Reuse (SBCARS), pp. 20–29 (2013)

  57. Pohl, K., Böckle, G., van der Linden, F.J.: Software Product Line Engineering: Foundations, Principles and Techniques. Springer, New York (2005)

    Book  Google Scholar 

  58. Pol’la, M., Buccella, A., Cechich, A.: Automated analysis of variability models: The sevatax process. In: Computational Science and Its Applications—ICCSA 2018—18th International Conference, Melbourne, VIC, Australia, July 2-5, 2018, Proceedings, Part IV, pp. 365–381 (2018)

  59. Rincón, L.F., Giraldo, G.L., Mazo, R., Salinesi, C.: An ontological rule-based approach for analyzing dead and false optional features in feature models. Electron. Not. Theor. Comput. Sci. 302, 111–132 (2014)

    Article  Google Scholar 

  60. Rincón, L., Giraldo, G., Mazo, R., Salinesi, C., Diaz, D.: Method to identify corrections of defects on product line models. Electron. Not. Theor. Comput. Sci. 314, 61–81 (2015). (CLEI 2014, the XL Latin American Conference in Informatic)

    Article  Google Scholar 

  61. Ripon, S., Piash, M.M., Hossain, S.M.A., Uddin, M.S.: Semantic web based analysis of product line variant model. Int. J. Comput. Electr. Eng. 6(1), 1 (2014)

    Article  Google Scholar 

  62. Roos-Frantz, F., Galindo, J.A., Benavides, D., Ruiz Cortés, A.: Fama-ovm: a tool for the automated analysis of ovms. In: Proceedings of the 16th International Software Product Line Conference—Volume 2, pp. 250–254. ACM (2012)

  63. Roos-frantz, F., Benavides, D., Ruiz-cortés, A.: Feature model to orthogonal variability model transformation towards interoperability between tools

  64. Sannella, M.: Skyblue: a multi-way local propagation constraint solver for user interface construction. In: Proceedings of the 7th Annual ACM Symposium on User Interface Software and Technology, UIST’94, pp. 137–146. ACM, New York (1994)

  65. Sinnema, M., Deelstra, S.: Industrial validation of COVAMOF. J. Syst. Softw. 81(4), 584–600 (2008)

    Article  Google Scholar 

  66. Sjoeberg, D.I.K., Hannay, J.E., Hansen, O., Kampenes, V.B., Karahasanovic, A., Liborg, N., Rekdal, A.C.: A survey of controlled experiments in software engineering. IEEE Trans. Softw. Eng. 31(9), 733–753 (2005)

    Article  Google Scholar 

  67. Sree-Kumar, A., Planas, E., Clariso, R.: Analysis of feature models using alloy: A survey. In: Proceedings 7th International Workshop on Formal Methods and Analysis in Software Product Line Engineering, FMSPLE@ETAPS 2016, Eindhoven, The Netherlands, April 3, 2016, pp. 46–60 (2016)

  68. Von Der Massen, T., Lichter, H.: Deficiencies in feature models. In: Proceedings of the Workshop on Software Variability Management for Product Derivation-Towards Tool Support (2004)

  69. Teixeira, L., Borba, P., Gheyi, R.: Safe composition of configuration knowledge-based software product lines. J. Syst. Softw. 86(4), 1038–1053 (2013). (SI: Software Engineering in Brazil: Retrospective and Prospective Views)

    Article  Google Scholar 

  70. Thaker, S., Batory, D., Kitchin, D., Cook, W.: Safe composition of product lines. In: Proceedings of the 6th International Conference on Generative Programming and Component Engineering, GPCE’07, pp. 95–104. ACM, New York (2007)

  71. Thüm, T., Apel, S., Kästner, C., Schaefer, I., Saake, G.: A classification and survey of analysis strategies for software product lines. ACM Comput. Surv. 47(1), 6:1–6:45 (2014)

    Article  Google Scholar 

  72. Thurimella, A.K., Janzen, D.: Metadoc feature modeler: a plug-in for ibm rational doors. In: 15th International Conference of Software Product Line (SPLC), pp. 313–322 (2011)

  73. Tomassetti, F., Torchiano, M., Tiso, A., Ricca, F., Reggio, G.: Maturity of software modelling and model driven engineering: a survey in the Italian industry. In: IET Conference Proceedings, pp. 91–100(9) (2012)

  74. Trinidad, P., Benavides, D., Ruiz Cortés, A., Segura, S., Jimenez, A.: FAMA framework. In: Proceedings of the International Software Product Line Conference. IEEE Computer Society, p. 359 (2008)

  75. Trujillo-Tzanahua, G.I., Juárez-Martínez, U., Alberto Alfonso, A.-L., Cortés-Verdín, M.K.: Multiple software product lines: applications and challenges. In: Mejia, J., Muñoz, M., Rocha, Á., Quiñonez, Y., Calvo-Manzano, J. (eds.) Trends and Applications in Software Engineering, pp. 117–126. Springer International Publishing, Cham (2018)

    Chapter  Google Scholar 

  76. van den Broek, P., Galvão, I.: Analysis of feature models using generalised feature trees. In: VaMoS, volume 29 of ICB Research Report, pp. 29–35. Universität Duisburg-Essen (2009)

  77. van der Linden, F., Schmid, K., Rommes, E.: Software Product Lines in Action: The Best Industrial Practice in Product Line Engineering. Springer, New York (2007)

    Book  Google Scholar 

  78. Wang, B., Xiong, Y., Hu, Z., Zhao, H., Zhang, W., Mei, H.: Interactive inconsistency fixing in feature modeling. J. Comput. Sci. Technol. 29(4), 724–736 (2014)

    Article  Google Scholar 

  79. Wang, H.H., Li, Y.F., Sun, J., Zhang, H., Pan, J.: Verifying feature models using owl. Web Semant. Sci. Serv. Agents World Wide Web 5(2), 117–129 (2007). (Software Engineering and the Semantic Web)

    Article  Google Scholar 

  80. Whittle, J., Hutchinson, J., Rouncefild, M., Burden, H., Heldal, R.: Industrial adoption of model-driven engineering: are the tools really the problem? In: Moreira, A., Schätz, B., Gray, J., Vallecillo, A., Clarke, P. (eds.) Model-Driven Engineering Languages and Systems, pp. 1–17. Springer, Berlin (2013)

    Google Scholar 

  81. Zaid, L., Kleinermann, F., De Troyer, O., Applying semantic web technology to feature modeling. In: Proceedings of the 2009 ACM Symposium on Applied Computing, SAC’09, pp. 1252–1256. ACM, New York (2009)

  82. Zhang, H., Babar, M.A., Tell, P.: Identifying relevant studies in software engineering. Inf. Softw. Technol. 53(6), 625–637 (2011). (Special Section: Best papers from the APSEC)

    Article  Google Scholar 

  83. Zhou, X., Jin, Y., Zhang, H., Li, S., Huang, X.: A map of threats to validity of systematic literature reviews in software engineering. In: 2016 23rd Asia-Pacific Software Engineering Conference (APSEC), pp. 153–160 (2016)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Agustina Buccella.

Additional information

Communicated by Andrzej Wasowski.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This work is partially supported by the UNComa Project 04/F009 “Reuso de Software orientado a Dominios—Parte II” part of the program “Desarrollo de Software Basado en Reuso—Parte II”.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pol’la, M., Buccella, A. & Cechich, A. Analysis of variability models: a systematic literature review. Softw Syst Model 20, 1043–1077 (2021). https://doi.org/10.1007/s10270-020-00839-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10270-020-00839-w

Keywords

Navigation