Using Colorimetric Concepts for the Evaluation of Goal Models
Using Colorimetric Concepts for the Evaluation of Goal Models
复制标题
使用比色概念评估目标模型
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Julio Cesar Sampaio do Prado Leite
中科院分区：
文献类型：
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作者：
R. Oliveira;Julio Cesar Sampaio do Prado Leite
面向目标的模型已成为分析非功能要求（NFR）的重要工具。但是，考虑到这类要求涵盖了质量特征，对NFR的处理是一项非平凡的任务。这意味着，在处理主观要求时，我们需要专注于可以丰富其代表语义的机制。在评估目标模型中，分配和传播标签是这种情况。现有模型上标签的定义具有较低的粒度，并且通常无法反映这种工具所能提供的全部形式潜力。 NFR框架就是这种情况。模型中的传播是机器人 - 启动，并且对目标的满足程度的理解变得困难。本文探讨了使用SIG中比色的概念（Softgoal Intectiondectiongency图），以增加分配给目标标签的信息能力。我们讨论颜色如何减轻增加目标模型分析粒度的挑战，从而改善对这些模型的评估。
Goal-oriented models have become important tools for the analysis of non-functional requirements (NFRs). However, the treatment of NFRs is a non-trivial task, considering that this class of requirements covers quality characteristics. This implies that when dealing with subjective requirements, we need to focus on mechanisms that can enrich the semantics of their representation. This is the case of assigning and propagating labels in the evaluation of goal-oriented models. The definition of labels on existing models has low granularity and often fails to reflect the full in-formational potential that this type of artifact could offer. This is the case of the NFR Framework. Propagation in the model is bot-tom-up and understanding about the degree of satisficing a goal becomes difficult. This paper explores a rationale to increase the informative power of the labels assigned to the goals, using the concepts of colorimetry in the SIG (Softgoal Interdependency Graph). We discuss how color may mitigate the challenge of increasing the granularity of goal models analysis, thus improving the evaluation of these models.