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ORPLocator: Identifying Read Points of Configuration Options via Static Analysis

机译:orplocator:通过静态分析识别配置选项的读取点

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Configuration options are widely used for customizing the behavior and initial settings of software applications, server processes, and operating systems. Their distinctive property is that each option is processed, defined, and described in different parts of a software project - namely in code, in configuration file, and in documentation. This creates a challenge for maintaining project consistency as it evolves. It also promotes inconsistencies leading to misconfiguration issues in production scenarios. We propose an approach for detection of inconsistencies between source code and documentation based on static analysis. Our approach automatically identifies source code locations where options are read, and for each such location retrieves the name of the option. Inconsistencies are then detected by comparing the results against the option names listed in documentation. We evaluated our approach on multiple components of Apache Hadoop, a complex framework with more than 800 options. Our tool ORPLocator was able to successfully locate at least one read point for 93% to 96% of documented options within four Hadoop components. A comparison with a previous state-of-the-art technique shows that our tool produces more accurate results. Moreover, our evaluation has uncovered 4 previously unknown, real-world inconsistencies between documented options and source code.
机译:配置选项广泛用于自定义软件应用程序,服务器进程和操作系统的行为和初始设置。它们的独特属性是每个选项都在软件项目的不同部分处理,定义和描述 - 即代码,配置文件和文档中的代码。这为维持项目一致性的发展而产生了挑战。它还促进了导致生产方案中的错误配置问题的不一致。我们提出了一种基于静态分析检测源代码与文档之间不一致的方法。我们的方法会自动识别读取选项的源代码位置,以及每个此类位置检索选项的名称。然后通过将结果与文档中列出的选项名称进行比较来检测不一致。我们在Apache Hadoop的多个组件中评估了我们的方法,这是一个超过800个选项的复杂框架。我们的工具Orpocator能够在四个Hadoop组件中成功定位至少一个读取点93%至96%的记录选项。与先前的最先进技术的比较表明,我们的工具会产生更准确的结果。此外,我们的评估已经发现了4个以前未知的现实世界不一致,在记录的选项和源代码之间。

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