User Perception of Numeric Contribution Semantics for Goal Models: An Exploratory Experiment

  • Norah Alothman
  • Mehrnaz Zhian
  • Sotirios LiaskosEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10650)


Goal models have long been regarded to be an effective way for representing stakeholder goals and how they relate to one another during requirements engineering. One of the ways goals are connected in goal models is contribution relationships, which represent how satisfaction of one goal affects the satisfaction of another. There are several proposals in the literature on how contributions should be modelled and used, but little empirical evidence as to which one is more intuitive for users. We experimentally explore how users interpret numeric contribution labels in goal models. Experimental participants are exposed to a number of pre-constructed goal models and are asked what they believe the satisfaction degree of a goal is given the satisfaction degree of other goals in the model. We find that users tend to prefer specific aggregation rules over others, depending, also, on specific factors.


Goal models Model comprehension Decision support 


  1. 1.
    Amyot, D., Ghanavati, S., Horkoff, J., Mussbacher, G., Peyton, L., Yu, E.S.K.: Evaluating goal models within the goal-oriented requirement language. Int. J. Intell. Syst. 25(8), 841–877 (2010)CrossRefGoogle Scholar
  2. 2.
    Amyot, D., Mussbacher, G.: User requirements notation: the first ten years, the next ten years. J. Softw. (JSW) 6(5), 747–768 (2011)Google Scholar
  3. 3.
    Baresi, L., Pasquale, L., Spoletini, P.: Fuzzy goals for requirements-driven adaptation. In: Proceedings of the 18th IEEE International Requirements Engineering (RE 2010), Sydney, Australia, pp. 125–134 (2010)Google Scholar
  4. 4.
    Caire, P., Genon, N., Heymans, P., Moody, D.L.: Visual notation design 2.0: towards user comprehensible requirements engineering notations. In: Proceedings of the 21st IEEE International Requirements Engineering Conference (RE 2013), pp. 115–124 (2013)Google Scholar
  5. 5.
    Crump, M.J.C., McDonnell, J.V., Gureckis, T.M.: Evaluating Amazon’s mechanical turk as a tool for experimental behavioral research. PLoS ONE 8(3), 1–18 (2013)CrossRefGoogle Scholar
  6. 6.
    Cruz-Lemus, J.A., Genero, M., Manso, M.E., Morasca, S., Piattini, M.: Assessing the understandability of UML statechart diagrams with composite states–a family of empirical studies. Empirical Softw. Eng. 14(6), 685–719 (2009)CrossRefGoogle Scholar
  7. 7.
    Elahi, G., Yu, E.S.K.: Requirements trade-offs analysis in the absence of quantitative measures: a heuristic method. In: Proceedings of the 2011 ACM Symposium on Applied Computing (SAC 2011), TaiChung, Taiwan, pp. 651–658 (2011)Google Scholar
  8. 8.
    Friendly, M., Meyer, D.: Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data. Chapman Hall, New York (2015)CrossRefGoogle Scholar
  9. 9.
    Giorgini, P., Mylopoulos, J., Nicchiarelli, E., Sebastiani, R.: Formal reasoning techniques for goal models. In: Spaccapietra, S., March, S., Aberer, K. (eds.) Journal on Data Semantics I. LNCS, vol. 2800, pp. 1–20. Springer, Heidelberg (2003). doi: 10.1007/978-3-540-39733-5_1CrossRefGoogle Scholar
  10. 10.
    Giorgini, P., Mylopoulos, J., Sebastiani, R.: Goal-oriented requirements analysis and reasoning in the Tropos methodology. Eng. Appl. Artif. Intell. 18(2), 159–171 (2005)CrossRefGoogle Scholar
  11. 11.
    Hadar, I., Reinhartz-Berger, I., Kuflik, T., Perini, A., Ricca, F., Susi, A.: Comparing the comprehensibility of requirements models expressed in use case and Tropos: results from a family of experiments. Inf. Softw. Technol. 55(10), 1823–1843 (2013)CrossRefGoogle Scholar
  12. 12.
    Horkoff, J., Yu, E.: Analyzing goal models: different approaches and how to choose among them. In: Proceedings of the 2011 ACM Symposium on Applied Computing (SAC 2011), TaiChung, Taiwan, pp. 675–682 (2011)Google Scholar
  13. 13.
    Horkoff, J., Yu, E.S.K.: Interactive goal model analysis for early requirements engineering. Requirements Eng. 21(1), 29–61 (2016)CrossRefGoogle Scholar
  14. 14.
    van Lamsweerde, A.: Reasoning about alternative requirements options. In: Borgida, A.T., Chaudhri, V.K., Giorgini, P., Yu, E.S. (eds.) Conceptual Modeling: Foundations and Applications. LNCS, vol. 5600, pp. 380–397. Springer, Heidelberg (2009). doi: 10.1007/978-3-642-02463-4_20CrossRefGoogle Scholar
  15. 15.
    Letier, E., van Lamsweerde, A.: Reasoning about partial goal satisfaction for requirements and design engineering. In: Proceedings of the 12th International Symposium on the Foundation of Software Engineering, FSE 2004, pp. 53–62 (2004)Google Scholar
  16. 16.
    Li, F.L., Horkoff, J., Mylopoulos, J., Guizzardi, R.S.S., Guizzardi, G., Borgida, A., Liu, L.: Non-functional requirements as qualities, with a spice of ontology. In: Proceedings of the 22nd International Requirements Engineering Conference (RE 2014), Karlskrona, Sweden, pp. 293–302 (2014)Google Scholar
  17. 17.
    Liaskos, S., Jalman, R., Aranda, J.: On eliciting preference and contribution measures in goal models. In: Proceedings of the 20th International Requirements Engineering Conference (RE 2012), Chicago, IL, pp. 221–230 (2012)Google Scholar
  18. 18.
    Liaskos, S., Khan, S.M., Soutchanski, M., Mylopoulos, J.: Modeling and reasoning with decision-theoretic goals. In: Ng, W., Storey, V.C., Trujillo, J.C. (eds.) ER 2013. LNCS, vol. 8217, pp. 19–32. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-41924-9_3CrossRefGoogle Scholar
  19. 19.
    Maiden, N., Pavan, P., Gizikis, A., Clause, O., Kim, H., Zhu, X.: Making decisions with requirements: integrating i* goal modelling and the AHP. In: Proceedings of the 8th International Working Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2002), Essen, Germany (2002)Google Scholar
  20. 20.
    Mylopoulos, J., Chung, L., Liao, S., Wang, H., Yu, E.: Exploring alternatives during requirements analysis. IEEE Softw. 18(1), 92–96 (2001)CrossRefGoogle Scholar
  21. 21.
    Mylopoulos, J., Chung, L., Nixon, B.: Representing and using nonfunctional requirements: a process-oriented approach. IEEE Trans. Softw. Eng. 18(6), 483–497 (1992)CrossRefGoogle Scholar
  22. 22.
    Norman, D.: The Design of Everyday Things. Basic Books, New York (2013)Google Scholar
  23. 23.
    Payne, S.J.: A descriptive study of mental models. Behav. Inf. Technol. 10(1), 3–21 (1991)CrossRefGoogle Scholar
  24. 24.
    Purchase, H.C., Welland, R., McGill, M., Colpoys, L.: Comprehension of diagram syntax: an empirical study of entity relationship notations. Int. J. Hum. Comput. Stud. 61(2), 187–203 (2004)CrossRefGoogle Scholar
  25. 25.
    Yu, E.S.K.: Towards modelling and reasoning support for early-phase requirements engineering. In: Proceedings of the 3rd IEEE International Symposium on Requirements Engineering (RE 1997), Annapolis, MD, pp. 226–235 (1997)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Norah Alothman
    • 1
  • Mehrnaz Zhian
    • 1
  • Sotirios Liaskos
    • 1
    Email author
  1. 1.York UniversityTorontoCanada

Personalised recommendations