解释为什么方法一起改变

A. Lozano, Carlos Noguera, V. Jonckers
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引用次数: 3

摘要

通过分析来自源代码管理系统的历史信息,以前的研究已经观察到某些方法倾向于一致地一起更改。Co-change被认为是一个很好的预测器,可以预测哪些实体可能会受到变化的影响,哪些可能缺少修改,哪些可能在未来发生变化。然而,现有的共变分析并没有提供为什么方法总是共变的见解。能够识别解释共同变更的基本原理可以允许记录和执行设计知识。本文提出了一种自动推导共变背后原因的方法。我们将一组共变的原因定义为共变元素所共有的一组属性。我们考虑两种属性:表明显式依赖关系的结构属性和揭示隐式依赖关系的语义属性。然后,我们试图找出单次提交背后的原因,以及反复影响同一组方法的共同更改背后的原因。这些方法集由集群方法标识,这些方法往往在相同的提交事务中被修改。我们对两个开源系统的历史进行了分析,分析了近19000种方法和超过3700次提交。我们表明,自动提取共同变化的解释是可能的,当考虑到结构和语义属性时,以及当分析的方法周期性地共同变化时,这种解释的质量会得到改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Explaining Why Methods Change Together
By analyzing historical information from Source Code Management systems, previous research has observed that certain methods tend to change together consistently. Co-change has been identified as a good predictor of the entities that are likely to be affected by a change, which ones might be missing modifications, and which ones might change in the future. However, existing co-change analysis provides no insight on why methods consistently co-change. Being able to identify the rationale that explains co-changes could allow to document and enforce design knowledge. This paper proposes an automatic approach to derive the reason behind a co-change. We define the reason of a (set) of co-changes as a set of properties common to the elements that co-change. We consider two kinds of properties: structural properties which indicate explicit dependencies, and semantic properties which reveal implicit dependencies. Then we attempt to identify the reasons behind single commits, as well as the reasons behind co-changes that repeatedly affect the same set of methods. These sets of methods are identified by clustering methods that tend to be modified in the same commit-transactions. We perform our analysis over the history of two open-source systems, analyzing nearly 19.000 methods and over 3700 commits. We show that it is possible to automatically extract explanations for co-changes, that the quality of such explanations improves when structural and semantic properties are taken into account, and when the methods analyzed co-change recurrently.
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