使用模型查询的反模式检测:方法的比较

Z. Ujhelyi, Á. Horváth, Dániel Varró, Norbert Istvan Csiszár, Gábor Szoke, László Vidács, R. Ferenc
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引用次数: 14

摘要

程序查询在一些软件进化任务中扮演着重要的角色,比如程序理解、影响分析,或者复杂重构操作的反模式的自动识别。这些任务的中心工件是由源代码(通常是语义图,ASG)构建的反向工程程序模型,该模型通常由专门的手工编码查询进行后处理。我们的论文研究了流行的工业Eclipse建模框架(EMF)作为程序模型的底层表示的使用,该程序模型由基于本地Java代码、本地搜索和增量求值的三种通用模型查询技术处理。我们在17个Java项目的源代码上对这些技术进行了深入的比较,这些技术使用的查询来自不同使用配置文件中的重构操作。我们的结果表明,通用模型查询的性能比手工编码查询高出2-3个数量级,而内存消耗和模型加载时间增加了5-10倍。此外,使用概要文件的度量结果可以用作在具体场景中选择适当查询技术的指导方针。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Anti-pattern detection with model queries: A comparison of approaches
Program queries play an important role in several software evolution tasks like program comprehension, impact analysis, or the automated identification of anti-patterns for complex refactoring operations. A central artifact of these tasks is the reverse engineered program model built up from the source code (usually an Semantic Graph, ASG), which is traditionally post-processed by dedicated, hand-coded queries. Our paper investigates the use of the popular industrial Eclipse Modeling Framework (EMF) as an underlying representation of program models processed by three general-purpose model query techniques based on native Java code, local-search and incremental evaluation. We provide in-depth comparison of these techniques on the source code of 17 Java projects using queries taken from refactoring operations in different usage profiles. Our results show that general purpose model queries outperform hand-coded queries by 2-3 orders of magnitude, while there is a 5-10 times increase in memory consumption and model load time. In addition, measurement results of usage profiles can be used as guidelines for selecting the appropriate query technologies in concrete scenarios.
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