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Mining packages change history to predict their future change-coupling behavior

机译:挖掘包更改历史记录以预测其未来的变更耦合行为

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In development and maintenance phases, packages of object oriented (OO) software applications are changed. During change process, change in one package in most of the cases will result in changes in other packages. The accurate prediction of future change-coupling behavior provides a significant challenge for development or maintenance team. In this paper, we have used association mining for analyzing the change history of the packages of an OO application and proposed an approach based on mining results and graph clustering for predicting change coupling. Firstly, a framework has been proposed to measure changeability index and change readiness of packages as well as frequently changed packages of an application. Secondly, package clustering has been done to generate clusters of packages that are highly change-coupled. A case study on a Java application has been done to demonstrate our work as well as to analyze the results. The results obtained from this study show that the proposed approach can be an essential aid for development team to predict future change-coupling behavior of packages.
机译:在开发和维护阶段,更改面向对象(OO)软件应用程序的包。在更改过程中,大多数情况下的一个包中的更改将导致其他包的变化。对未来变更耦合行为的准确预测为开发或维护团队提供了重大挑战。在本文中,我们使用了协会挖掘来分析OO应用程序包的变化历史,并提出了一种基于挖掘结果和图形聚类来预测变化耦合的方法。首先,已经提出了一个框架来测量可变性指数并改变包的准备,以及频繁更改的应用程序。其次,已经完成了包群集以生成高度改变耦合的包的集群。已经完成了关于Java申请的案例研究以展示我们的工作以及分析结果。本研究中获得的结果表明,该方法可以是开发团队预测包装的未来改变耦合行为的必要援助。

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