Abstract
Multiple-criteria decision making (MCDM) is widely used in ranking choices from a set of available alternatives with respect to multiple criteria. To analytically rank requirements under various criteria, we propose a tool called requirements prioritizer (RP) which has the capacity of keeping records of project stakeholders with their relative weights against each requirement, utilized by the system to compute an ordered list of prioritized requirements. The proposed approach offers a novel way of involving stakeholders in the entire decision making process irrespective of their numbers in an automated fashion. In this proposed approach, the relative weights assigned by each stakeholder are normalized and aggregated. The output of the system consists of prioritized requirements with an automatically generated graph showing the relative values of requirements across project stakeholders in a chronological order.
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References
Perini, A., Angelo, S., Paolo, A.: A machine learning approach to software requirements prioritization. IEEE Transactions on Software Engineering 39(4), 445–461 (2013)
Karlsson, L., Thelin, T., Regnell, B., Berander, P., Wohlin, C.: Pair-wise comparisons versus planning game partitioning – experiments on requirements prioritisation techniques. Empirical Software Engineering 12(1), 3–33 (2007)
Karlsson, J.: Software requirements prioritizing. In: Proceedings of 2nd International Conference on Requirements Engineering, pp. 110–116 (1996)
Lehtola, L., Kauppinen, M.: Empirical evaluation of two requirements prioritization methods in Product Development Projects. In: Proc. European Software Process Improvement Conference, Trondheim, Norway, pp. 161–170 (2004)
Perini, A., Ricca, F., Susi, A.: Tool-supported requirements prioritization: comparing the AHP and CBRank methods. Information and Software Technology 51(6), 1021–1032 (2009)
Avesani, P., Bazzanella, C., Perini, A., Susi, A.: Facing scalability issues in requirements prioritization with machine learning techniques. In: Proceedings of 13th IEEE International Conference on Requirements Engineering, Paris, France, pp. 297–306. IEEE Computer Society (2005)
Berander, P., Andrews, A.: Requirements prioritization. In: A. Aurum, C. Wohlin (Eds.), Engineering and Managing Software Requirements. Springer (2005)
Karlsson, J., Wohlin, C., Regnell, B.: An evaluation of methods for prioritizing software requirements. Information and Software Technology 39, 14–15 (1998)
Karlsson, J., Ryan, K.: A cost-value approach for prioritizing requirements. IEEE Software 14(5), 939–947 (1997)
Voola, P., Vinaya Babu, A.: Interval evidential reasoning algorithm for requirements prioritization. In: Satapathy, S.C., Avadhani, P.S., Abraham, A. (eds.) Proceedings of the InConINDIA 2012. AISC, vol. 132, pp. 915–922. Springer, Heidelberg (2012)
Khari, M., Nikunj, K.: Comparison of six prioritization techniques for software requirements. Journal of Global Research in Computer Science 4(1), 38–43 (2013)
Achimugu, P., Selamat, A., Ibrahim, R., Mahrin, M.N.: A systematic literature review of software requirements prioritization research. Information and Software Technology 56(6), 568–585 (2014)
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Achimugu, P., Selamat, A., Ibrahim, R. (2014). A Web-Based Multi-Criteria Decision Making Tool for Software Requirements Prioritization. In: Hwang, D., Jung, J.J., Nguyen, NT. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2014. Lecture Notes in Computer Science(), vol 8733. Springer, Cham. https://doi.org/10.1007/978-3-319-11289-3_45
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DOI: https://doi.org/10.1007/978-3-319-11289-3_45
Publisher Name: Springer, Cham
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