Imprecisions Diagnostic in Source Code Deltas

Guillermo De la Torre, R. Robbes, Alexandre Bergel
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引用次数: 10

Abstract

Beyond a practical use in code review, source code change detection (SCCD) is an important component of many mining software repositories (MSR) approaches. As such, any error or imprecision in the detection may result in a wrong conclusion while mining repositories. We identified, analyzed, and characterized impressions in GumTree, which is the most advanced algorithm for SCCD. After analyzing its detection accuracy over a curated corpus of 107 C# projects, we diagnosed several imprecisions. Many of our findings confirm that a more language-aware perspective of GumTree can be helpful in reporting more precise changes.
源代码增量中的不精确诊断
除了在代码审查中的实际应用之外,源代码更改检测(SCCD)是许多挖掘软件存储库(MSR)方法的重要组成部分。因此,在挖掘存储库时,检测中的任何错误或不精确都可能导致错误的结论。我们在GumTree中识别、分析和表征印痕,这是SCCD中最先进的算法。在分析了107个c#项目的检测精度后,我们发现了一些不精确的地方。我们的许多发现都证实,一个更加语言感知的GumTree视角有助于报告更精确的变化。
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