A Joint Statistical Estimation of the RFC and CBO Metrics for Open-Source Applications Developed in Java

2022 IEEE 17th International Conference on Computer Sciences and Information Technologies (CSIT) Pub Date : 2022-11-10 DOI:10.1109/CSIT56902.2022.10000457

S. Prykhodko, N. Prykhodko, Tetiana Smykodub

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Abstract

The response for a class (RFC) and coupling between object classes (CBO) metrics, along with other ones, are used for evaluating software complexity, including object-oriented design (OOD) complexity of open-source applications (apps), providing a measure of the third step (the relationships between classes) in OOD. Recommended values for the RFC and CBO metrics are known without correlation between them. However, there is a correlation between the RFC and CBO metrics. That is why we have performed jointly estimating the RFC and CBO metrics for 46 open-source apps developed in Java. We have constructed a prediction ellipse for the normalized RFC and CBO metrics based on the bivariate Box-Cox normalizing transformation to aid software architects and designers in managing complexity in OOD. If the squared Mahalanobis distance for normalized values of the RFC and CBO metrics for an app is greater than 12.57, it means that there is high complexity due to the relationships between classes.

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用Java开发的开源应用程序的RFC和CBO度量的联合统计估计

类的响应(RFC)和对象类之间的耦合(CBO)指标，以及其他指标，用于评估软件复杂性，包括开源应用程序(app)的面向对象设计(OOD)复杂性，提供OOD中第三步(类之间关系)的度量。RFC和CBO指标的推荐值是已知的，它们之间没有相关性。然而，RFC和CBO指标之间存在相关性。这就是为什么我们对46个用Java开发的开源应用程序的RFC和CBO指标进行了联合评估。基于二元Box-Cox归一化转换，构建了归一化RFC和CBO指标的预测椭圆，以帮助软件架构师和设计人员管理OOD中的复杂性。如果应用的RFC和CBO指标的规格化值的马氏距离的平方大于12.57，则意味着由于类之间的关系存在很高的复杂性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2022 IEEE 17th International Conference on Computer Sciences and Information Technologies (CSIT)

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