Detecting anti-patterns in Java EE runtime system model

Lei Zhang, Yanchun Sun, Hui Song, Weihu Wang, Gang Huang
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引用次数: 5

Abstract

With the increasing complexity of enterprise applications, it becomes very challenging to create software systems which can exhibit a satisfactory performance behavior. In current system development practice, it often inevitably exists some "anti-patterns", which usually impede the performance or maintainability of software systems. Manually investigating anti-patterns in systems is a time-consuming and labor intensive task. To deal with this problem, we propose a general anti-pattern detection approach for Java EE application. Firstly, we propose a Java EE meta-model, based on which, we use QVT language to specify the detection process of anti-patterns. Secondly, we implement our approach on a runtime architecture-based reflective framework. When a Java EE application runs on one of the supported application servers, we can execute QVT script to detect whether or not there exists a specific anti-pattern in current system and get the report of potential problem components. At last, we perform a case study based on 35 well-known anti-patterns to evaluate the effectiveness and applicability of our approach.
检测Java EE运行时系统模型中的反模式
随着企业应用程序的日益复杂,如何创建能够表现出令人满意的性能行为的软件系统变得非常具有挑战性。在当前的系统开发实践中,往往不可避免地存在一些“反模式”,这些“反模式”通常会阻碍软件系统的性能或可维护性。手动调查系统中的反模式是一项耗时且劳动密集型的任务。为了解决这个问题,我们为Java EE应用程序提出了一种通用的反模式检测方法。首先,我们提出了一个Java EE元模型,在此基础上,我们使用QVT语言指定反模式的检测过程。其次,我们在基于运行时体系结构的反射框架上实现我们的方法。当Java EE应用程序在其中一个受支持的应用服务器上运行时,我们可以执行QVT脚本来检测当前系统中是否存在特定的反模式,并获得潜在问题组件的报告。最后,我们基于35个著名的反模式进行了一个案例研究,以评估我们的方法的有效性和适用性。
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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