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Prediction of Software Maintainability Using Fuzzy Logic

机译:基于模糊逻辑的软件可维护性预测

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摘要

The relationship between object oriented metrics and software maintainability is complex and non-linear. Therefore, there is considerable research interest in development and application of sophisticated techniques which can be used to build models for predicting software maintainability. However, when predicting maintainability not only product quality measurements are surrounded with imprecision and uncertainty, but also the relationships between the external and internal quality attributes suffer from imprecision and uncertainty. The reason behind that, there are at least two important sources of information for building the prediction mode): historical data and human experts. Therefore, in this paper an attempt has been made to utilize the capability of fuzzy logic in handling imprecision and uncertainty to come up with an efficient maintainability prediction model. The proposed model is constructed using object-oriented metrics data in Li and Henry's datasets collected from two different object-oriented systems.
机译:面向对象的度量标准与软件可维护性之间的关系是复杂且非线性的。因此,对于可用于构建用于预测软件可维护性的模型的复杂技术的开发和应用具有相当大的研究兴趣。但是,在预测可维护性时,不仅产品质量测量中存在不精确性和不确定性,而且外部和内部质量属性之间的关系也受到不精确性和不确定性的影响。其背后的原因是,至少有两个重要的信息来源可用于构建预测模式:历史数据和人类专家。因此,本文尝试利用模糊逻辑处理不精确性和不确定性的能力来提出有效的可维护性预测模型。利用从两个不同的面向对象系统收集的Li和Henry数据集中的面向对象的度量数据,构造了所提出的模型。

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