2019
DOI: 10.1093/comjnl/bxy143
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Game Theory-Based Reasoning of Opposing Non-functional Requirements using Inter-actor Dependencies

Abstract: Goal-oriented requirements engineering frameworks are used to model stakeholders’ objectives and requirements using goals. In a real-time environment, stakeholders’ requirements may have opposing objectives. Hence, a novel framework is needed that captures the real issues in order to achieve multi-objective optimization of inter-dependent actors. For obtaining an optimum strategy for inter-dependent actors in the i* goal model, a multi-objective two-person zero-sum game theory-based approach is applied in this… Show more

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Cited by 10 publications
(2 citation statements)
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References 27 publications
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“…In cloud applications, determining NFR, workload, and Quality of Service (QoS) must be considered in deciding technology infrastructure [12]. Sumesh et al's study sought to achieve multi-objective optimisation of interdependent stakeholders and developed a framework to capture the competing NFR goals [13]. Soter [14], a method for modeling and translating NFR models, was introduced by DeVries and Cheng.…”
Section: B Non-functional Requirementsmentioning
confidence: 99%
“…In cloud applications, determining NFR, workload, and Quality of Service (QoS) must be considered in deciding technology infrastructure [12]. Sumesh et al's study sought to achieve multi-objective optimisation of interdependent stakeholders and developed a framework to capture the competing NFR goals [13]. Soter [14], a method for modeling and translating NFR models, was introduced by DeVries and Cheng.…”
Section: B Non-functional Requirementsmentioning
confidence: 99%
“…This approach utilizes function nets contained in candidate architectures to derive main event chains of the system under development [39]. In 2019, Sumesh et al presented a framework to capture the opposing NFR goals to achieve multi-objective optimization of inter-dependent stakeholders [40].…”
Section: Related Work a Nfr Assuring Approachesmentioning
confidence: 99%