Towards an Ontology-Based Approach for Eliciting Possible Solutions to Non-Functional Requirements

  • Rodrigo Veleda
  • Luiz Marcio CysneirosEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11483)


Requirements Engineering plays a crucial role in the software development process. Many works have pointed out that Non-Functional Requirements (NFRs) are critical to the quality of software systems. NFRs, also known as quality requirements, can be difficult to elicit due to their subjective diversity nature. In this paper, we introduce the QR Framework which uses an ontology-based approach to support the collection of knowledge on possible solutions to implement NFRs, semi-automatically connecting related NFRs. Preliminary search mechanisms are provided in a tool to facilitate the identification of possible solutions to an NFR and their related consequences to other solutions and/or other NFRs. To evaluate whether our approach aids eliciting NFRs, we conducted a controlled experiment performing a software development scenario. Our results suggest that reusing NFR knowledge can drive software engineers to obtain a closer to complete set of possible solutions to address quality concerns.


Non-Functional Requirements Knowledge reuse Ontology Quality requirements 



This research was partially supported by NSERC. We would also like to thank the valuable comments received from the reviewers for improving the paper.


  1. 1.
    Hasan, M.M., Loucopoulos, P., Nikolaidou, M.: Classification and qualitative analysis of non-functional requirements approaches. In: Bider, I., et al. (eds.) BPMDS/EMMSAD -2014. LNBIP, vol. 175, pp. 348–362. Springer, Heidelberg (2014). Scholar
  2. 2.
    Chung, L., Nixon, B.A., Yu, E., Mylopoulos, J.: Non-Functional requirements in software engineering. International Series in Software Engineering, vol. 5. Springer, Boston (2000). Scholar
  3. 3.
    Webster, I., Ivanova, V., Cysneiros, L.M.: Reusable knowledge for achieving privacy: health information technologies perspective. In: Proceedings of Requirements Engineering, Porto, Portugal, vol. 112, pp. 752–972 (2005). ISBN 0790Google Scholar
  4. 4.
    Cysneiros, L.M.: Evaluating the effectiveness of using catalogues to elicit non-functional requirements. In: WER, pp. 107–115 (2007)Google Scholar
  5. 5.
    Cardoso, E., Almeida, J.P., Guizzardi, R.S., Guizzardi, G.: A method for eliciting goals for business process models based on non-functional requirements catalogues. In: Frameworks for Developing Efficient Information Systems: Models, Theory, and Practice: Models, Theory, and Practice, pp. 226–242 (2013)CrossRefGoogle Scholar
  6. 6.
    de Gramatica, M., Labunets, K., Massacci, F., Paci, F., Tedeschi, A.: The role of catalogues of threats and security controls in security risk assessment: an empirical study with ATM professionals. In: Fricker, S.A., Schneider, K. (eds.) REFSQ 2015. LNCS, vol. 9013, pp. 98–114. Springer, Cham (2015). Scholar
  7. 7.
    Lopez, C., Cysneiros, L.M., Astudillo, H.: NDR ontology: sharing and reusing NFR and design rationale knowledge. In: 2008 1st International Workshop on Managing Requirements Knowledge, MARK 2008 (2008)Google Scholar
  8. 8.
    Veleda, R., Cysneiros, L.M.: Towards a tool to help exploring existing non-functional requirements solution patterns. In: 2017 IEEE 25th International Requirements Engineering Conference Workshops (REW), pp. 232–239. IEEE (2017)Google Scholar
  9. 9.
    Cleland-Huang, J., Settimi, R., Benkhadra, O., Berezhanskaya, E., Christina, S.: Goal-centric traceability for managing non-functional requirements. In: Proceedings of the 27th International Conference on Software Engineering, New York, NY, USA, pp. 362–371. ACM (2005)Google Scholar
  10. 10.
    Supakkul, S., Hill, T., Chung, L., Tun, T.T., do Prado Leite, J.C.S.: An NFR pattern approach to dealing with NFRs. In: 2010 18th IEEE International Requirements Engineering Conference, pp. 179–188. IEEE (2010)Google Scholar
  11. 11.
    Sancho, P.P., Juiz, C., Puigjaner, R., Chung, L., Subramanian, N.: An approach to ontology-aided performance engineering through NFR framework. In: Proceedings of the 6th International Workshop on Software and Performance, New York, NY, USA, pp. 125–128. ACM (2007)Google Scholar
  12. 12.
    Van Harmelen, F., McGuinness, D.: OWL web ontology language overview. W3C Recommendation (2004)Google Scholar
  13. 13.
    Al Balushi, T.H., Sampaio, P.R.F., Dabhi, D., Loucopoulos, P.: ElicitO: a quality ontology-guided NFR elicitation tool. In: Sawyer, P., Paech, B., Heymans, P. (eds.) REFSQ 2007. LNCS, vol. 4542, pp. 306–319. Springer, Heidelberg (2007). Scholar
  14. 14.
    Hu, H., Ma, Q., Zhang, T., Tan, Y., Xiang, H., Fu, C., Feng, Y.: Semantic modelling and automated reasoning of non-functional requirement conflicts in the context of softgoal interdependencies. IET Softw. 9, 145–156 (2015)CrossRefGoogle Scholar
  15. 15.
    Brickley, D., Guha, R.V: RDF Vocabulary Description Language 1.0: RDF Schema (2002).
  16. 16.
    The W3C SPARQL Working Group: SPARQL Query Language for RDF.
  17. 17.
    Berners-Lee, T., Hendler, J., Lassila, O., et al.: The semantic web. Sci. Am. 284, 28–37 (2001)CrossRefGoogle Scholar
  18. 18.
    Salman, I., Misirli, A.T., Juristo, N.: Are students representatives of professionals in software engineering experiments? In: 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, pp. 666–676. IEEE (2015)Google Scholar
  19. 19.
    Feldt, R., et al.: Four commentaries on the use of students and professionals in empirical software engineering experiments. Empir. Softw. Eng. 23, 3801–3820 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Information TechnologyYork UniversityTorontoCanada

Personalised recommendations