Abstract:Requirement elicitation is an important activity in early requirement engineering. Several wellknown approaches and goal models have been developed to deal with requirement elicitation. The i* goal model is used to represent the socio-technical domains and can be used for analysis in early requirement analysis. The elicitation process is complicated by the incomplete and imprecise input data available for analysis. Imprecise and unavailable data can be captured by fuzzy logic and then it can be managed by the popular operation research techniques known as optimisation. This paper presents a formal multiobjective optimisation model, for the i* framework, with regard to requirement elicitation. The optimisation model has the capacity to handle large and complex systems. The optimisation model has been expanded to include sensitivity analysis, in order to facilitate useful information on input data for the requirement analyst. The proposed approach is explained using the London Ambulance System case study and is evaluated using a simulation based analysis.

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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 paper, by balancing the opposing goals reciprocally. The proposed approach involves the generation of each objective function based on the inter-dependency relationships, the creation of decision pay-off matrices based on the objective function values and their variation to a final decision pay-off matrix. A Maxmin solution is formulated for the multi-objective game model, in which the optimization problem for each player is a linear programming problem. Finally, the most desirable strategies and their proportion values are found. By integrating Java with the IBM CPLEX optimization tool, a simulation model based on the proposed method was developed. A successful evaluation was conducted on various case studies from the existing literature. Evaluation results indicate that the developed simulation model helps users to choose an optimal alternative design option feasible in real-time competitive environments that have goals with opposing objectives.

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