Guiding Identification of Missing Scenarios for Dynamic Feature Location

Shinpei Hayashi, H. Kazato, Takashi Kobayashi, T. Oshima, Katsuyuki Natsukawa, T. Hoshino, M. Saeki
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引用次数: 4

Abstract

Feature location (FL) is an important activity for finding correspondence between software features and modules in source code. Although dynamic FL techniques are effective, the quality of their results depends on analysts to prepare sufficient scenarios for exercising the features. In this paper, we propose a technique for guiding identification of missing scenarios using the prior FL result. After applying FL, unexplored call dependencies are extracted by comparing the results of static and dynamic analyses, and analysts are advised to investigate them for finding missing scenarios. We propose several metrics that measure the potential impact of unexplored dependencies to help analysts sort out them. Through a preliminary evaluation using an example web application, we showed our technique was effective for recommending the clues to find missing scenarios.
动态特征定位中缺失场景的指导性识别
特性定位(FL)是在源代码中查找软件特性和模块之间的对应关系的重要活动。尽管动态FL技术是有效的,但其结果的质量取决于分析人员准备充分的场景来行使这些特征。在本文中,我们提出了一种利用先前的FL结果指导识别缺失场景的技术。在应用FL之后,通过比较静态和动态分析的结果来提取未探索的调用依赖关系,并建议分析人员调查它们以找到缺失的场景。我们提出了几个度量未开发依赖性的潜在影响的度量标准,以帮助分析人员对它们进行分类。通过使用一个示例web应用程序进行初步评估,我们证明了我们的技术在推荐线索以查找缺失场景方面是有效的。
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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