Software & Systems Modeling

, Volume 18, Issue 5, pp 3025–3047 | Cite as

Student experience with software modeling tools

  • Luciane T. W. Agner
  • Timothy C. LethbridgeEmail author
  • Inali W. Soares
Regular Paper


Modeling is a key concept in software engineering education, since students need to learn it in order to be able to produce large-scale and reliable software. Quality tools are needed to support modeling in education, but existing tools vary considerably both in their features and in their strengths and weaknesses. The objective of the research presented in this paper was to help professors and students choose tools by determining which strengths and weaknesses matter most to students, which tools exhibit which of these strengths and weaknesses, and how difficult to use are various tools for students. To achieve this objective, we conducted a survey of the use of modeling tools among students in software engineering courses from Brazil, Canada, USA, Spain, Denmark, UK and China. We report the results regarding the 31 UML tools that 117 participants have used, focusing on the nine tools that the students have used most heavily. Common benefits quoted by students in choosing a tool include simplicity of installing and learning, being free, supporting the most important notations and providing code generation. The most cited complaints about tools include lack of feedback, being slow to use, difficulty drawing the diagrams, not interacting well with other tools and being complex to use. This research also compares the results with the findings of another survey conducted among professors who taught modeling. The results should benefit tool developers by suggesting ways they could improve their tools. The results should also help inform the selection of tools by educators and students.


Software modeling tools Software engineering education Survey 



We would like to thank all the participants in this survey and the professors who forwarded the survey to their students. Dr. Lethbridge’s research is funded in part by NSERC.


  1. 1.
    Paige, R.F., Polack, F.A., Kolovos, D.S., Rose, L.M., Matragkas, N., Williams, J.R.: Bad modelling teaching practices. In: ACM/IEEE 17th International Conference on Model Driven Engineering Languages and Systems—Educators Symposium, Valencia, Spain (2014)Google Scholar
  2. 2.
    Akayama, S., Demuth, B., Lethbridge, T.C., Scholz, M., Stevens, P., Stikkolorum, D.R.: Tool use in software modelling education. In: Proceedings of the ACM/IEEE 16th International Conference on Model Driven Engineering Languages and Systems—Educators Symposium, Miami, USA (2013)Google Scholar
  3. 3.
    Budgen, D., Burn, A.J., Brereton, O.P., Kitchenham, B.A., Pretorius, R.: Empirical evidence about the UML: a systematic literature review. Softw. Pract. Exp. 41(4), 363–392 (2011)CrossRefGoogle Scholar
  4. 4.
    Forward, A., Badreddin, O., Lethbridge, T.C.: Perceptions of software modeling: a survey of software practitioners. In: Proceedings of the 5th Workshop from Code Centric to Model Centric: Evaluating the Effectiveness of MDD (C2 M:EEMDD) (2010)Google Scholar
  5. 5.
    Agner, L.T.W., Lethbridge, T.C.: A survey of tool use in modeling education. In: Proceedings of the ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS), pp. 303–311 (2017)Google Scholar
  6. 6.
    Reggio, G., Leotta, M., Ricca, F.: Who knows/uses what of the UML: a personal opinion survey. Models 2014, pp. 140–165. Springer, Berlin (2014)Google Scholar
  7. 7.
    Kuzniarz, L., Martins, L.E.G.: Teaching model-driven software development: a pilot study. In: Proceedings of the ITiCSE Working Group Reports (ITiCSE ‘16). ACM, New York, NY, USA, pp. 45–56 (2016)Google Scholar
  8. 8.
    Tekinerdogan, B.: Experience in teaching a graduate course on model-driven software development. Comput. Sci. Educ. 21(4), 363–387 (2013)CrossRefGoogle Scholar
  9. 9.
    Paige, R.F., Polack, F.A., Kolovos, D.S., Rose, L.M., Matragkas, N., Williams, J.R.: Bad modelling teaching practices. In: Proceedings of the ACM/IEEE 17th International Conference on Model Driven Engineering Languages and Systems—Educators Symposium (Educators’ Symposium@MODELS) (2014)Google Scholar
  10. 10.
    Lethbridge, T.C.: Teaching modeling using Umple: principles for the development of an effective tool. In: Proceedings of the IEEE 27th Conference on Software Engineering Education and Training (CSEE&T), pp. 23–28 (2014)Google Scholar
  11. 11.
    Lynch, A., Flango, D., Smith, R., Lang, M.: Experiences of using Rational Rose/Visio for UML modeling in an undergraduate software engineering course: a student perspective. J. Comput. Sci. Coll. 19(5), 353–356 (2004)Google Scholar
  12. 12.
    Liebel, G., Heldal, R., Steghöfer, J.P.: Impact of the use of industrial modelling tools on modelling education. In: Proceedings of the IEEE 29th International Conference on Software Engineering Education and Training (CSEET’16), Dallas, TX, pp. 18–27 (2016)Google Scholar
  13. 13.
    Giraldo, F.D., España, S., Giraldo W.J., Pastor, O.: Modelling language quality evaluation in model-driven information systems engineering: a roadmap. In: IEEE 9th International Conference Research Challenges in Information Science (RCIS), pp. 64–69, IEEE (2015)Google Scholar
  14. 14.
    Whittle, J., Hutchinson, J., Rouncefield, M.: The state of practice in model-driven engineering. IEEE Softw. 31(3), 79–85 (2014)CrossRefGoogle Scholar
  15. 15.
    Mussbacher, G., Amyot, D., Breu, R., Bruel, J.M., Cheng, B.H., Collet, P., et al.: The relevance of model-driven engineering thirty years from now. In: Proceeding of the 17th International Conference ACM/IEEE—Conference on Model Driven Engineering Languages and Systems (MODELS). LNCS, vol. 8767, pp. 183–200, Springer (2014)Google Scholar
  16. 16.
    Tomassetti, F., Tiso, A., Ricca, F., Torchiano, M., Reggio, G.: Maturity of software modelling and model driven engineering: A survey in the Italian industry. In: Proceeding of 16th International Conference on Evaluation Assessment in Software Engineering (EASE), pp. 91–100 (2012)Google Scholar
  17. 17.
    Weisstein, E.W.: Bonferroni correction. MathWorld—a Wolfram web resource. CRC Press. Accessed October 2018
  18. 18.
    Gérard, S., Dumoulin, C., Tessier, P., Selic, B.: Papyrus: A UML2 tool for domain-specific language modeling. In: Giese, H., Karsai, G., Lee, E., Rumpe, B., Schätz, B. (eds.) Model-Based Engineering of Embedded Real-Time Systems. LNCS, vol. 6100, pp. 361–368. Springer, Berlin (2010)CrossRefGoogle Scholar
  19. 19.
    Lanusse, A., Tanguy, Y., Espinoza, H., Mraidha, C., Gerard, S., Tessier, P., Schnekenburger, R., Dubois, H., Terrier, F.: Papyrus UML: an open source toolset for MDA. In: Proceedings of the 5th European Conference on Model-Driven Architecture Foundations and Applications (ECMDA-FA 2009), pp. 1–4 (2009)Google Scholar
  20. 20.
    Lethbridge, T.C., Abdelzad, V., Husseini Orabi, M., Husseini Orabi, A., Adesina, O.: Merging modeling and programming using Umple. In: Margaria, T., Steffen, B. (eds.) Leveraging Applications of Formal Methods, Verification and Validation: Discussion, Dissemination, Applications (ISoLA 2016). LNCS, vol. 9953, pp. 187–197. Springer, Berlin (2016)CrossRefGoogle Scholar
  21. 21.
    Gogolla, M., Büttner, F., Richters, M.: USE: a UML-based specification environment for validating UML and OCL. Sci. Comput. Program. 69, 27–34 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  22. 22.
    Mussbacher, G., Amyot, D.: Goal and scenario modeling, analysis, and transformation with jUCMNav. Software Engineering-Companion Volume, 2009. In: 31st International Conference on Software Engineering (ICSE), IEEE, pp. 431–432 (2009)Google Scholar
  23. 23.
    Duran, M.B., Mussbacher, G.: Evaluation of goal models in reuse hierarchies with delayed decisions. In: IEEE 25th International Requirements Engineering Conference Workshops (REW), IEEE, pp. 6–15 (2017)Google Scholar
  24. 24.
    Sallam, R.L., Richardson, J., Hagerty, J., Hostmann, B.: Magic quadrant for business intelligence platforms. Gartner Group, Stamford (2011)Google Scholar
  25. 25.
    Montgomery, D.C., Runger, G.C., Hubele, N.F.: Engineering statistics. Wiley, New York (2009)Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceMid-West State University (UNICENTRO)GuarapuavaBrazil
  2. 2.Electrical Engineering and Computer ScienceUniversity of OttawaOttawaCanada

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