利用模糊逻辑支持软件进化

L. Cerulo, Raffaele Esposito, M. Tortorella, L. Troiano
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引用次数: 5

摘要

确定遗留软件系统演进的策略需要分析和评估活动。在决定应用最合适的策略时,必须考虑软件系统的性能和成本信息。已经定义了许多方法来支持这一任务,并且一些作者已经提出了帮助选择进化策略的决策框架。这些方法往往缺乏管理不确定性的技术,不确定性传统上被认为是不科学的,是错误的来源,是由答复者提供的答案的信心引起的。利用模糊逻辑概念对先前提出的方法进行了分析和扩展。该方法使用基于目标-问题-度量(GQM)范式的度量框架和一组批评表。在这两个组件中都引入了模糊逻辑原则,以便更好地了解所分析的软件系统质量,并指出当采用一种选择的策略而不是另一种策略时要承担的风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Supporting software evolution by using fuzzy logic
Identifying a strategy for legacy software system evolution requires analysis and assessment activities. Information on performance and costs of software systems must be considered when making decisions on the most suitable strategy to be applied. Many approaches have been defined for supporting this task, and several authors have proposed decision frameworks for aiding the selection of evolution strategy. These approaches often lack of techniques for the management of uncertainty, traditionally considered as unscientific and as a source of errors and arising from the confidence of the answers provided by respondents. An approach previously proposed is analyzed and extended with fuzzy logic concepts. The approach uses a measurement framework based on the Goal-Question-Metric (GQM) paradigm and a set of critiquing tables. Fuzzy logic principles have been introduced in both components, for obtaining a better insight of the analyzed software system quality and an indication of the risks to be assumed when one selected strategy is adopted instead of another.
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