Reflection on Evolutionary Decision Making with Goal Modeling Via Empirical Studies

A. Grubb
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引用次数: 3

Abstract

Goal models have long been used in academia without wide spread adoption in industry. If the fundamental purpose of goal models is to allow stakeholders to generate scenarios and ask "what if" questions, then which parts of the process of model construction, analysis, and evolution benefit from and which are hindered by manual activities? The recent expansion of goal modelling to ask time-based questions further amplifies this issue because significant additional information is required from stakeholders. Through a series of empirical studies, we aim to isolate the processes of model construction, analysis, and evolution for the purpose of studying the utility of goal-oriented requirements engineering approaches and exploring which tasks are essential practices that stakeholders must complete themselves to gain modeling benefit, and which tasks can be simplified through automation. In this process, we will also measure the benefits of completing relevant goal modelling activities with and without timing analysis. In this short communication, we describe our objectives for understanding the benefits of and barriers to goal-oriented requirements engineering.
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基于目标模型的进化决策实证研究
目标模型在学术界使用时间较长,但在产业界并未得到广泛采用。如果目标模型的基本目的是允许涉众生成场景并提出“如果”的问题,那么模型构建、分析和进化过程的哪些部分从中受益,哪些部分受到手工活动的阻碍?最近扩展目标建模以提出基于时间的问题进一步放大了这个问题,因为需要利益相关者提供重要的额外信息。通过一系列的实证研究,我们旨在分离模型构建、分析和进化的过程,以研究面向目标的需求工程方法的效用,并探索哪些任务是涉众必须自己完成才能获得建模利益的基本实践,以及哪些任务可以通过自动化来简化。在这个过程中,我们还将测量在有和没有时间分析的情况下完成相关目标建模活动的好处。在这个简短的交流中,我们描述了我们的目标,以理解面向目标的需求工程的好处和障碍。
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