An Approach Based on Intuitionistic Fuzzy Sets for Considering Stakeholders’ Satisfaction, Dissatisfaction, and Hesitation in Software Features Prioritization

Vassilis C. Gerogiannis (), Dimitrios Tzimos, George Kakarontzas, Eftychia Tsoni, Omiros Iatrellis, Le Hoang Son and Andreas Kanavos ()
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Vassilis C. Gerogiannis: Department of Digital Systems, University of Thessaly, 41500 Larissa, Greece
Dimitrios Tzimos: Department of Digital Systems, University of Thessaly, 41500 Larissa, Greece
George Kakarontzas: Department of Digital Systems, University of Thessaly, 41500 Larissa, Greece
Eftychia Tsoni: Department of Informatics, Open Hellenic University, 26335 Patras, Greece
Omiros Iatrellis: Department of Digital Systems, University of Thessaly, 41500 Larissa, Greece
Le Hoang Son: VNU Information Technology Institute, Vietnam National University, Hanoi 03000, Vietnam
Andreas Kanavos: Department of Informatics, Ionian University, 49100 Corfu, Greece

Mathematics, 2024, vol. 12, issue 5, 1-36

Abstract: This paper introduces a semi-automated approach for the prioritization of software features in medium- to large-sized software projects, considering stakeholders’ satisfaction and dissatisfaction as key criteria for the incorporation of candidate features. Our research acknowledges an inherent asymmetry in stakeholders’ evaluations, between the satisfaction from offering certain features and the dissatisfaction from not offering the same features. Even with systematic, ordinal scale-based prioritization techniques, involved stakeholders may exhibit hesitation and uncertainty in their assessments. Our approach aims to address these challenges by employing the Binary Search Tree prioritization method and leveraging the mathematical framework of Intuitionistic Fuzzy Sets to quantify the uncertainty of stakeholders when expressing assessments on the value of software features. Stakeholders’ rankings, considering satisfaction and dissatisfaction as features prioritization criteria, are mapped into Intuitionistic Fuzzy Numbers, and objective weights are automatically computed. Rankings associated with less hesitation are considered more valuable to determine the final features’ priorities than those rankings with more hesitation, reflecting lower indeterminacy or lack of knowledge from stakeholders. We validate our proposed approach with a case study, illustrating its application, and conduct a comparative analysis with existing software requirements prioritization methods.

Keywords: software requirements prioritization; software features prioritization; binary search tree prioritization; stakeholder satisfaction; stakeholder dissatisfaction; stakeholder hesitation; stakeholder uncertainty; Intuitionistic Fuzzy Sets (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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