基于文本和基于依赖的bug起源确定技术的初步评估

Steven Davies, M. Roper, M. Wood
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引用次数: 4

摘要

了解软件bug生命周期的关键一步是确定它们的起源。不幸的是,这些信息通常不会被记录下来,并且在以后的日期恢复它是具有挑战性的。最近出现了两种尝试解决这个问题的方法:文本方法和依赖关系方法。然而,到目前为止,对它们的有效性进行的评估有限,部分原因是缺乏将bug与它们的引入联系起来的数据集。由于问题的主观性,生成这样的数据集既耗时又具有挑战性。为了改进这一点,我们手动识别了两个开源项目中166个bug的来源。然后将这些方法与模拟方法进行比较。结果表明,这两种方法在各种不同类型的bug中都取得了部分成功。他们的准确率达到了29% - 79%,召回率达到了40% - 70%,如果结合起来,效果会更好。然而,在未来的开发中仍有许多挑战需要克服——大量提交、不相关的更改以及原始版本和修复之间的大量版本都会降低它们的有效性。
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A Preliminary Evaluation of Text-based and Dependency-based Techniques for Determining the Origins of Bugs
A crucial step in understanding the life cycle of software bugs is identifying their origin. Unfortunately this information is not usually recorded and recovering it at a later date is challenging. Recently two approaches have been developed that attempt to solve this problem: the text approach and the dependency approach. However only limited evaluation has been carried out on their effectiveness so far, partially due to the lack of data sets linking bugs to their introduction. Producing such data sets is both time-consuming and challenging due to the subjective nature of the problem. To improve this, the origins of 166 bugs in two open-source projects were manually identified. These were then compared to a simulation of the approaches. The results show that both approaches were partially successful across a variety of different types of bugs. They achieved a precision of 29% -- 79% and a recall of 40% -- 70%, and could perform better when combined. However there remain a number of challenges to overcome in future development -- large commits, unrelated changes and large numbers of versions between the origin and the fix all reduce their effectiveness.
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