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Toward comprehensible software defect prediction models using fuzzy logic

机译：运用模糊逻辑建立可理解的软件缺陷预测模型

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摘要

Software defect prediction is a discipline that predicts the defects proneness of future modules. Software metrics are used for this kind of predication. However, the predication metrics are associated with uncertainty, thus the metrics need to be expressed in linguistic terms to overcome ambiguity and uncertainty. Two types of knowledge are utilized as input to the prediction models: software metrics and expert's opinions. This paper proposes a framework for developing fuzzy logic-based software predication model using different set of software metrics. It aims to provide a generic set of metrics to be used for software defects prediction. The performance of the proposed Fuzzy-based models has been validated using real software projects data where Takagi-Sugeno fuzzy inference engine is used to predict software defects. Validation results are satisfactory.
机译：软件缺陷预测是一门可以预测未来模块的缺陷倾向的学科。软件指标用于此类预测。但是，谓词度量与不确定性相关联，因此需要用语言表达度量以克服歧义和不确定性。两种类型的知识被用作预测模型的输入：软件指标和专家意见。本文提出了使用不同的软件度量集来开发基于模糊逻辑的软件预测模型的框架。它旨在提供一组通用的度量标准，以用于软件缺陷预测。已使用真实的软件项目数据验证了所提出的基于模糊模型的性能，其中使用Takagi-Sugeno模糊推理引擎来预测软件缺陷。验证结果令人满意。

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