Nazim, Mohd. and Mohammad, Chaudhary Wali and Sadiq, Mohd (2022) Fuzzy-Based Methods for the Selection and Prioritization of Software Requirements: A Systematic Literature Review. In: 9th International Conference on Frontiers in Intelligent Computing: Theory and Applications, FICTA 2021, 25-26 June 2021, Aizawl, pp. 115-129.
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Software requirements (SRs) selection is one of the major research issues in the field of software engineering which is used to select the requirements from the list of the elicited SRs on the basis of their ranks. There are different fuzzy-based techniques for computing the ranking values of SRs. Based on our review, we found different studies which focus on the literature review of the SRs selection and prioritization. There is no study which synthesizes the SRs selection methods under a fuzzy environment. Therefore, to address this issue, this paper presents a systematic literature review (SLR) in the area of fuzzy-based methods for the selection of SRs. Four research questions (RQs) have been formulated to identify the research gaps in the literature: RQ1: What are the different fuzzy-based methods for the selection of the SRs? RQ2: Which fuzzy number is mostly used during the computation process? RQ3: What kinds of datasets have been used in the SRs selection methods? RQ4: Which system/application has been used to select the SRs? Search items were extracted from the Journals, Conferences, and Workshops based on the RQs. Our SLR has identified 54 different studies. Selected studies were accessed based on the RQs thus identifying the research issues in the literature. After the analysis of the 54 studies, it was identified that the area of SRs selection has lots of research issues which can be addressed by applying the other soft computing techniques to find out the ranking order of SRs.
| Item Type: | Conference Paper |
|---|---|
| Publisher: | Springer Science and Business Media Deutschland GmbH |
| Additional Information: | The copyright of this article belongs to the Springer Science and Business Media Deutschland GmbH. |
| Department/Centre: | Division of Electrical Sciences > Computer Science & Automation |
| Date Deposited: | 23 May 2022 04:54 |
| Last Modified: | 23 May 2022 04:54 |
| URI: | https://eprints.iisc.ac.in/id/eprint/72409 |
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