应用模糊逻辑减少软件开发过程中的量化误差和上下文偏差问题

F. Marcelloni, M. Aksit
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引用次数: 12

摘要

面向对象方法定义了相当数量的规则,这些规则通常使用二值逻辑表示。例如,需求规范中的实体作为一个类要么被接受,要么被拒绝。在当前的方法中,规则的定义和应用存在两个主要问题。首先,二值逻辑不能有效地表达典型软件开发过程的近似性和不精确性。其次,上下文因素对规则的影响一般没有明确建模。我们将这些问题分别称为量化误差和上下文偏差问题。为了减少这些问题,我们采用了基于模糊逻辑的方法规则。该方法与方法无关,可用于评价和改进现有方法。此外,模糊逻辑的使用增加了设计模型的适应性和可重用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reducing quantization error and contextual bias problems in software development processes by applying fuzzy logic
Object-oriented methods define a considerable number of rules, which are generally expressed using two-valued logic. For example, an entity in a requirement specification is either accepted or rejected as a class. There are two major problems of how rules are defined and applied in current methods. Firstly, two-valued logic cannot effectively express the approximate and inexact nature of a typical software development process. Secondly, the influence of contextual factors on rules is generally not modeled explicitly. We term these problems as quantization error and contextual bias problems, respectively. To reduce these problems, we adopt fuzzy logic-based methodological rules. This approach is method independent and is useful for evaluating and enhancing current methods. In addition, the use of fuzzy logic increases the adaptability and reusability of design models.
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