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Identifying Changed Source Code Lines from Version Repositories

机译:从版本库中识别更改的源代码行

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Observing the evolution of software systems at different levels of granularity has been a key issue for a number of studies, aiming at predicting defects or at studying certain phenomena, such as the presence of clones or of crosscutting concerns. Versioning systems such as CVS and SVN, however, only provide information about lines added or deleted by a contributor: any change is shown as a sequence of additions and deletions. This provides an erroneous estimate of the amount of code changed. This paper shows how the evolution of changes at source code line level can be inferred from CVS repositories, by combining information retrieval techniques and the Levenshtein edit distance. The application of the proposed approach to the ArgoUML case study indicates a high precision and recall.
机译:观察软件系统在不同粒度级别上的发展已成为许多研究的关键问题,旨在预测缺陷或研究某些现象,例如克隆的存在或横切关注点。但是,诸如CVS和SVN的版本控制系统仅提供有关由贡献者添加或删除的行的信息:任何更改都显示为添加和删除的顺序。这会错误估计更改的代码量。本文展示了如何通过结合信息检索技术和Levenshtein编辑距离来从CVS存储库中推断源代码行级别的更改演变。拟议的方法在ArgoUML案例研究中的应用表明具有很高的准确性和召回率。

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