Context and Motivation: The notion of goal and goal models is ideal for the alternative systems. Goal models provide us different alternatives during goal oriented requirements engineering. Question/Problem: Once we find different alternatives, we need to evaluate these alternatives to select the best one. Ideas: The selection process consists of two main parts. In first part of the selection process among alternatives, we will use techniques in which we establish some evaluation criteria. The evaluation criteria are based on leaf level goals. Stakeholders are involved to contribute their opinions about the evaluation criteria. The input provided by various stakeholders is then converted into quantifiable numbers using fuzzy triangle numbers. After applying the defuzzification process on fuzzy triangle numbers we get scores (weights) for each criteria. In second part, these scores are used in the selection process to select the best alternative. Contribution: The two steps selection process helps us to select the best alternative among many alternatives. We have described the process and applied it to "cyclecomputer" selection case study.
Abstract-Software quality requirements are essential part for the success of software development. Defined and guaranteed quality in software development requires identifying, refining, and predicting quality properties by appropriate means. Goal models of goal oriented requirements engineering (GORE) and quality models are useful for modelling of functional goals as well as for quality goals. Once the goal models are obtained representing the functional requirements and integrated quality goals, there is need to evaluate each functional requirement arising from functional goals and quality requirement arising from quality goals. The process consist of two main parts. In first part, the goal models are used to evaluate functional goals. The leaf level goals are used to establish the evaluation criteria. Stakeholders are also involved to contribute their opinions about the importance of each goal (functional and/or quality goal). Stakeholder opinions are then converted into quantifiable numbers using triangle fuzzy numbers (TFN). After applying the defuzzification process on TFN, the scores (weights) are obtained for each goal. In second part specific quality goals are identified, refined/tailored based on existing quality models and their evaluation is performed similarly using TFN and by applying defuzzification process. The two step process helps to evaluate each goal based on stakeholder opinions and to evaluate the impact of quality requirements. It also helps to evaluate the relationships among functional goals and quality goals. The process is described and applied on 'cyclecomputer' case study.
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