Toward Development Framework for Eliciting and Documenting Knowledge in Requirements Elicitation

  • Halah A. Al-AlsheikhEmail author
  • Hessah A. Alsalamah
  • Abdulrahman A. Mirza
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1045)


Requirements engineering (RE) is the most critical factor in the success or failure of project. A project’s success completely depends on the knowledge and experience of the stakeholders. RE is a team-based process and collaborative task, which involves a huge volume of deliberation and discussion between stakeholders, and comes from their tacit knowledge. During the RE process, the presence of unclear or hidden tacit knowledge causes ambiguity, incomplete, and incorrect requirements. To address these issues, we intended to propose a collaborative knowledge management system framework for identifying, categorizing, eliciting, and managing the requirements tacit knowledge that are required for software development. This work proposes a framework that is based on a combination of rationale-based model and domain ontology. In this paper, a comparison between some of methods that have been used for requirements elicitation and tacit knowledge elicitation with the proposed framework as an evaluation method was presented.


Requirements engineering Requirements elicitation process Tacit knowledge Rationale-based model Domain ontology 


  1. 1.
    Wong, L.R., Mauricio, D.S., Rodriguez, G.D.: A systematic literature review about software requirements elicitation. J. Eng. Sci. Technol. 12(2), 296–317 (2017)Google Scholar
  2. 2.
    Femmer, H.: Requirements engineering artifact quality: definition and control, Ph.D. Thesis, Technische Universität München (2017)Google Scholar
  3. 3.
    Sukumaran, S. Chandran, K.: The unspoken Requirements-eliciting tacit knowledge as building blocks for knowledge management systems. In: Uden, L., et al. (eds.) Knowledge Management in Organizations 2015, LNBIP, vol. 224, pp. 26–40, Springer, Cham (2015)Google Scholar
  4. 4.
    Ferrari, A., Spoletini, P., Gnesi, S.: Ambiguity and tacit knowledge in requirements elicitation interviews. Requirements Eng. 21(3), 333–355 (2016)CrossRefGoogle Scholar
  5. 5.
    Vasanthapriyan, S., Tian, J., Xiang, J.: A survey on knowledge management in software engineering. In: 2015 IEEE International Conference on Software Quality, Reliability and Security-Companion (QRS-C). IEEE (2015)Google Scholar
  6. 6.
    Sánchez, K.O., Osollo, J.R., Martínez, L.F., Rocha, V.M.: Requirements engineering based on knowledge: a comparative case study of the KMoS-RE strategy and the DMS process. Rev. Fac. de Ingeniería 77, 88–94 (2015)Google Scholar
  7. 7.
    Emebo, O., Varde, A.S., Daramola, O.: Common sense knowledge, ontology and text mining for implicit requirements. In: International Conference on Data Mining (DMIN). The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp) (2016)Google Scholar
  8. 8.
    Sandhu, R.K., Weistroffer, H.R.: A review of fundamental tasks in requirements elicitation. In: Wrycza, S., Maślankowski, J. (eds.) SIGSAND/PLAIS 2018, LNBIP 333, pp. 31–44. Springer, Cham (2018)Google Scholar
  9. 9.
    Polanyi, M.: The Tacit Dimension. Routlege and Kegan, London (1966)Google Scholar
  10. 10.
    Coppedge, B.B.: Transferring tacit knowledge with the movement of people: a Delphi study. In: Business Administration, Ph.D. Thesis, University of Phoenix (2010)Google Scholar
  11. 11.
    Kotz, T., Smuts, H.: Model for knowledge capturing during system requirements elicitation in a high reliability organization: a case study. In: Proceedings of the Annual Conference of the South African Institute of Computer Scientists and Information Technologists, p. 305–312. ACM, Port Elizabeth, South Africa (2018)Google Scholar
  12. 12.
    Emebo, O., Olawande, D., Charles, A.: An automated tool support for managing implicit requirements using analogy-based reasoning. In: IEEE Tenth International Conference, Research Challenges in Information Science (RCIS), pp. 1–7. IEEE (2016)Google Scholar
  13. 13.
    Mohamed, A.H.: Facilitating tacit-knowledge acquisition within requirements engineering. In: Proceedings of the 10th WSEAS International Conference on Applied Computer Science (ACS’10), World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA (2010)Google Scholar
  14. 14.
    Pantförder, D., Schaupp, J., Vogel-Heuser, B.: Making implicit knowledge explicit—Acquisition of plant staff’s mental models as a basis for developing a decision support system. In: Stephanidis, C. (ed.) HCII Posters 2017, Part I, CCIS, vol. 13, pp. 358–365. Springer, Cham (2017)Google Scholar
  15. 15.
    Hao, J., Zhao, Q., Yan, Y., Wang, G.: A review of tacit knowledge: current situation and the direction to go. Int. J. Softw. Eng. Knowl. Eng. 27(05), 727–748 (2017)CrossRefGoogle Scholar
  16. 16.
    Castaneda, V., Ballejos, L., Caliusco, M., Galli, M.: The use of ontologies in requirements engineering. Glob. J. Res. In Eng. 10(6), 2–8 (2010)Google Scholar
  17. 17.
    Mohamed, K.A., Farhan, M.S., Elatif, M.M.A.A.: Ontology-based concept maps for software engineering. In: Computer Engineering Conference (ICENCO), 2013 9th International. IEEE (2013)Google Scholar
  18. 18.
    Schneider, L., Hajji, K., Schirbaum, A., Basten, D.: Knowledge creation in requirements engineering-a systematic literature review. In: International Proceedings on Proceedings Wirtschaftsinformatik, pp. 1829–1843 (2013)Google Scholar
  19. 19.
    Turban, B.: Rationale management and traceability in detailed discussion. In: Tool-Based Requirement Traceability between Requirement and Design Artifacts, pp 159–258. Springer Vieweg, Wiesbaden (2013)Google Scholar
  20. 20.
    Kurtanović, Z., Maalej, W.: On user rationale in software engineering. Requirements Eng. 23(3), 357–379 (2018)CrossRefGoogle Scholar
  21. 21.
    Maalej, W, Thurimella, A.K.: DUFICE: guidelines for a lightweight management of requirements knowledge. In: Maalej, W., Thurimella, A.K. (eds.) Managing Requirements Knowledge, pp. 75–91. Springer, Heidelberg (2013)Google Scholar
  22. 22.
    Dutoit, A.H., Paech, B.: Rationale-based use case specification. Requirements Eng. 7(1), 3–19 (2002)CrossRefGoogle Scholar
  23. 23.
    Liang, P., Avgeriou, P., He, K.: Rationale management challenges in requirements engineering. In: 2010 Third International Workshop on Managing Requirements Knowledge (MARK), pp. 16–21. IEEE, Sydney, Australia (2010)Google Scholar
  24. 24.
    Thurimella, A.K., et al.: Guidelines for managing requirements rationales. IEEE Softw. 34(1), 82–90 (2017)CrossRefGoogle Scholar
  25. 25.
    Maalej, W., Thurimella, A.K.: An Introduction to Requirements Knowledge. In: Maalej, W., Thurimella, A.K. (eds.) Managing Requirements Knowledge, pp. 1–20. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  26. 26.
    Bugaite, D., Vasilecas, O.: Framework on application domain ontology transformation into set of business rules. In: International Conference on Computer Systems and Technologies–CompSysTech (2005)Google Scholar
  27. 27.
    Haron, A., et al.: Understanding the requirement engineering for organization: the challenges. In: 8th International Conference on Computing Technology and Information Management (NCM and ICNIT), pp. 561–567. IEEE, Seoul, South Korea (2012)Google Scholar
  28. 28.
    MacLean, A., et al.: Questions, options, and criteria: elements of design space analysis. Hum. Comput. Interact. 6(3–4), 201–250 (1991)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Halah A. Al-Alsheikh
    • 1
    Email author
  • Hessah A. Alsalamah
    • 2
  • Abdulrahman A. Mirza
    • 3
  1. 1.Information Systems DepartmentAl Imam Mohammad Ibn Saud Islamic University (IMSIU)RiyadhSaudi Arabia
  2. 2.Information Systems DepartmentAl Yamamah UniversityRiyadhSaudi Arabia
  3. 3.Information Systems DepartmentKing Saud UniversityRiyadhSaudi Arabia

Personalised recommendations