FEVER:从提交中提取面向特性的更改

Nicolas Dintzner, A. Deursen, M. Pinzger
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引用次数: 14

摘要

研究高度可配置系统的演化需要彻底理解这些系统的三个核心成分:(1)潜在的变异性模型;(2)共同实现可配置特征的资产;(3)变量特征到实际资产的映射。不幸的是,到目前为止,还没有系统的方法可以在足够细粒度的级别上获得此类信息。为了解决这个问题,我们提出了FEVER及其在Linux内核中的实例化。FEVER提取关于可变性模型(KConfig文件)、资产(基于C代码的预处理器)和映射(Make- files)变化的详细信息。我们描述了FEVER的工作原理,并将其应用于几个Linux内核版本。我们对来自两个不同版本的300个随机选择的提交进行了评估,结果表明我们的结果在82.6%的提交中是准确的。此外,我们还说明了如何在典型的Linux工程任务中使用由此获得的填充的FEVER图形数据库。
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FEVER: Extracting Feature-oriented Changes from Commits
The study of the evolution of highly configurable systems requires a thorough understanding of thee core ingredients of such systems: (1) the underlying variability model; (2) the assets that together implement the configurable features; and (3) the mapping from variable features to actual assets. Unfortunately, to date no systematic way to obtain such information at a sufficiently fine grained level exists.To remedy this problem we propose FEVER and its instantiation for the Linux kernel. FEVER extracts detailed information on changes in variability models (KConfig files), assets (preprocessor based C code), and mappings (Make- files). We describe how FEVER works, and apply it to several releases of the Linux kernel. Our evaluation on 300 ran- domly selected commits, from two different releases, shows our results are accurate in 82.6% of the commits. Furthermore, we illustrate how the populated FEVER graph database thus obtained can be used in typical Linux engineering tasks.
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