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dc.contributor.authorDar, Hafsa
dc.contributor.authorAziz, Romana
dc.contributor.authorKhan, Javed Ali
dc.contributor.authorLali, Muhammad IkramUllah
dc.contributor.authorAlmujally, Nouf Abdullah
dc.date.accessioned2024-09-26T17:45:02Z
dc.date.available2024-09-26T17:45:02Z
dc.date.issued2024-09-19
dc.identifier.citationDar , H , Aziz , R , Khan , J A , Lali , M I & Almujally , N A 2024 , ' Gamify4LexAmb: a gamification-based approach to address lexical ambiguity in natural language requirements ' , PeerJ Computer Science , vol. 10 , e2229 , pp. 1-25 . https://doi.org/10.7717/peerj-cs.2229
dc.identifier.issn2376-5992
dc.identifier.urihttp://hdl.handle.net/2299/28269
dc.description© 2024 Dar et al. This is an open access article distributed under the Creative Commons Attribution License, to view a copy of the license, see: https://creativecommons.org/licenses/by/4.0/
dc.description.abstractAmbiguity is a common challenge in specifying natural language (NL) requirements. One of the reasons for the occurrence of ambiguity in software requirements is the lack of user involvement in requirements elicitation and inspection phases. Even if they get involved, it is hard for them to understand the context of the system, and ultimately unable to provide requirements correctly due to a lack of interest. Previously, the researchers have worked on ambiguity avoidance, detection, and removal techniques in requirements. Still, less work is reported in the literature to actively engage users in the system to reduce ambiguity at the early stages of requirements engineering. Traditionally, ambiguity is addressed during inspection when requirements are initially specified in the SRS document. Resolving or removing ambiguity during the inspection is time-consuming, costly, and laborious. Also, traditional elicitation techniques have limitations like lack of user involvement, inactive user participation, biases, incomplete requirements, etc. Therefore, in this study, we have designed a framework, Gamification for Lexical Ambiguity (Gamify4LexAmb), for detecting and reducing ambiguity using gamification. Gamify4LexAmb engages users and identifies lexical ambiguity in requirements, which occurs in polysemy words where a single word can have several different meanings. We have also validated Gamify4LexAmb by developing an initial prototype. The results show that Gamify4LexAmb successfully identifies lexical ambiguities in given requirements by engaging users in requirements elicitation. In the next part of our research, an industrial case study will be performed to understand the effects of gamification on real-time data for detecting and reducing NL ambiguity.en
dc.format.extent25
dc.format.extent447349
dc.language.isoeng
dc.relation.ispartofPeerJ Computer Science
dc.titleGamify4LexAmb: a gamification-based approach to address lexical ambiguity in natural language requirementsen
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionCybersecurity and Computing Systems
dc.contributor.institutionBiocomputation Research Group
dc.contributor.institutionDepartment of Computer Science
dc.description.statusPeer reviewed
rioxxterms.versionofrecord10.7717/peerj-cs.2229
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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