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

机译:挖掘包会更改历史记录,以预测其未来的更改耦合行为

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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,将更改面向对象(OO)软件应用程序的软件包。在更改过程中,大多数情况下更改一个程序包将导致其他程序包的更改。对未来变更耦合行为的准确预测为开发或维护团队提出了重大挑战。在本文中,我们使用关联挖掘来分析OO应用程序包的更改历史,并提出了一种基于挖掘结果和图聚类的方法来预测更改耦合。首先,已经提出了一种框架来测量可更改性指数和程序包以及应用程序经常更改的程序包的更改准备情况。其次,已经完成了程序包聚类以生成高度更改耦合的程序包聚类。已经对Java应用程序进行了案例研究,以演示我们的工作并分析结果。从这项研究中获得的结果表明,所提出的方法可以为开发团队预测包装的未来变更耦合行为提供必要的帮助。

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