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An Empirical Study of Long-Lived Code Clones

机译:长期代码克隆的实证研究

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Previous research has shown that refactoring code clones as soon as they are formed or discovered is not always feasible or worthwhile to perform, since some clones never change during evolution and some disappear in a short amount of time, while some undergo repetitive similar edits over their long lifetime. Toward a long-term goal of developing a recommendation system that selectively identifies clones to refactor, as a first step, we conducted an empirical investigation into the characteristics of long-lived clones. Our study of 13558 clone genealogies from 7 large open source projects, over the history of 33.25 years in total, found surprising results. The size of a clone, the number of clones in the same group, and the method-level distribution of clones are not strongly correlated with the survival time of clones. However, the number of developers who modified clones and the time since the last addition or removal of a clone to its group are highly correlated with the survival time of clones. This result indicates that the evolutionary characteristics of clones may be a better indicator for refactoring needs than static or spatial characteristics such as LOC, the number of clones in the same group, or the dispersion of clones in a system.
机译:先前的研究表明,重构或克隆代码克隆后,总是不可行或不值得执行,因为一些克隆在进化过程中从未发生变化,而在短时间内消失了,而一些对其进行了重复的类似编辑使用寿命长。为了实现开发推荐系统的长期目标,该系统可以选择性地识别要重构的克隆,第一步,我们对长寿命克隆的特征进行了实证研究。在总共33.25年的历史中,我们对7个大型开源项目的13558个克隆谱系进行了研究,结果令人惊讶。克隆的大小,同一组中的克隆数以及方法级别的克隆分布与克隆的生存时间没有很强的相关性。但是,修改克隆的开发人员的数量以及自从上次向其组中添加或删除克隆以来的时间与克隆的生存时间高度相关。该结果表明,与静态或空间特性(例如LOC,同一组中的克隆数量或系统中的克隆分散度)相比,克隆的进化特性可能是重构需求的更好指标。

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