瀑布:用于修复web应用程序的记录重放测试的增量方法

Mouna Hammoudi, G. Rothermel, Andrea Stocco
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引用次数: 47

摘要

软件工程师使用记录/重播工具来捕获用例场景,这些场景可以作为web应用程序的回归测试。然而,面对代码更改,这样的测试可能很脆弱。因此,研究人员一直在寻求自动化的方法来修复损坏的记录/重播测试。到目前为止,这种方法是通过直接分析web应用程序版本之间的差异来操作的。但是,在发布之间通常存在中间版本或提交,这些中间版本代表了细粒度的更改序列,新版本根据这些更改进行演化。在本文中,我们介绍了WATERFALL,这是一种增量测试修复方法,它在web应用程序的一系列细粒度版本中迭代地应用测试修复技术。对七个web应用程序的实证研究结果表明,我们的方法比粗粒度方法(总体209%)有效得多,同时保持了可接受的开销水平。
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WATERFALL: an incremental approach for repairing record-replay tests of web applications
Software engineers use record/replay tools to capture use case scenarios that can serve as regression tests for web applications. Such tests, however, can be brittle in the face of code changes. Thus, researchers have sought automated approaches for repairing broken record/replay tests. To date, such approaches have operated by directly analyzing differences between the releases of web applications. Often, however, intermediate versions or commits exist between releases, and these represent finer-grained sequences of changes by which new releases evolve. In this paper, we present WATERFALL, an incremental test repair approach that applies test repair techniques iteratively across a sequence of fine-grained versions of a web application. The results of an empirical study on seven web applications show that our approach is substantially more effective than a coarse-grained approach (209% overall), while maintaining an acceptable level of overhead.
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