在部署描述符中推断和应用类似自定义使用的配置耦合

Chengyuan Wen, Yaxuan Zhang, Xiao He, Na Meng
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引用次数: 3

摘要

当在Java框架(例如Spring)上构建企业应用程序时,开发人员通常使用一种名为“部署描述符(DD)”的特殊XML文件来指定组件和配置操作。维护这样的XML文件既困难又耗时;因为(1)正确的配置语义是特定于领域的,但通常是模糊的文档;(2)现有的编译器和程序分析工具很少检查XML文件。为了帮助开发人员确保DD的质量,本文提出了一种新颖的方法——xeditor,它从DD中提取配置耦合(即,经常共同发生的配置),并采用耦合规则来验证新的或更新的文件。Xeditor有两个阶段:耦合提取和bug检测。为了识别耦合,Xeditor首先在开源项目中挖掘DD,并提取(i)经常共存于相同文件中的XML实体对和(ii)至少保存一次相同数据的XML实体对。然后Xeditor对提取的对应用自定义关联规则挖掘。对于bug检测,给定一个新的XML文件,Xeditor检查该文件是否违反了任何耦合;如果是,Xeditor会报告违规行为。为了进行评估,我们首先用从1137个GitHub项目中挖掘的4248个DD创建了两个数据集。根据这些数据集的实验,Xeditor提取耦合的精度很高(73%);它检测漏洞的准确率为92%,召回率为96%,准确率为94%。此外,我们将Xeditor应用于另外478个GitHub项目的版本历史。Xeditor发现了25个非常可疑的XML更新,其中15个后来由开发人员修复。
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Inferring and Applying Def-Use Like Configuration Couplings in Deployment Descriptors
When building enterprise applications on Java frameworks (e.g., Spring), developers often specify components and configure operations with a special kind of XML files named “deployment descriptors (DD)”. Maintaining such XML files is challenging and time-consuming; because (1) the correct configuration semantics is domain-specific but usually vaguely documented, and (2) existing compilers and program analysis tools rarely examine XML files. To help developers ensure the quality of DD, this paper presents a novel approach-XEDITOR-that extracts configuration couplings (i.e., frequently co-occurring configurations) from DD, and adopts the coupling rules to validate new or updated files. Xeditor has two phases: coupling extraction and bug detection. To identify couplings, Xeditor first mines DD in open-source projects, and extracts XML entity pairs that (i) frequently coexist in the same files and (ii) hold the same data at least once. Xeditor then applies customized association rule mining to the extracted pairs. For bug detection, given a new XML file, Xeditor checks whether the file violates any coupling; if so, Xeditor reports the violation(s). For evaluation, we first created two data sets with the 4,248 DD mined from 1,137 GitHub projects. According to the experiments with these data sets, Xeditor extracted couplings with high precision (73%); it detected bugs with 92% precision, 96% recall, and 94% accuracy. Additionally, we applied Xeditor to the version history of another 478 GitHub projects. Xeditor identified 25 very suspicious XML updates, 15 of which were later fixed by developers.
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