Simultaneous Refactoring and Regression Testing

Jeffrey J. Yackley, M. Kessentini, G. Bavota, Vahid Alizadeh, Bruce Maxim
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引用次数: 1

Abstract

Currently, refactoring and regression testing are treated independently by existing studies. However, software developers frequently switch between these two activities, using regression testing to identify unwanted behavior changes introduced while refactoring and applying refactoring on identified buggy code fragments. Our hypothesis is that the tools to support developers in these two tasks could transfer part of the knowledge extracted from the process of finding refactoring opportunities to identify relevant test cases, and vice-versa. We propose a simultasking, search-based algorithm that unifies the tasks of refactoring and regression testing, hence solving them simultaneously and enabling knowledge transfer between them. The salient feature of the proposed algorithm is a unified and generic solution representation scheme for both problems, which serves as a common platform for knowledge transfer between them. We implemented and evaluated the proposed simultasking approach on six opensource systems and one industrial project. Our study features quantitative and qualitative analysis performed with developers, and the results achieved show that the proposed approach provides advantages over mono-task techniques treating refactoring and regression testing separately.
同时进行重构和回归测试
目前,重构和回归测试在现有的研究中是独立对待的。然而,软件开发人员经常在这两种活动之间切换,使用回归测试来识别重构时引入的不需要的行为更改,并对已识别的有缺陷的代码片段应用重构。我们的假设是,在这两个任务中支持开发人员的工具可以转移从寻找重构机会的过程中提取的部分知识,以识别相关的测试用例,反之亦然。我们提出了一种基于搜索的并行任务算法,该算法将重构和回归测试的任务统一起来,从而同时解决它们并实现它们之间的知识转移。该算法的显著特点是为这两个问题提供了统一的、通用的解表示方案,为这两个问题之间的知识转移提供了一个通用的平台。我们在六个开源系统和一个工业项目上实施并评估了所提出的并行处理方法。我们的研究特点是对开发人员进行定量和定性分析,结果表明,所提出的方法比单独处理重构和回归测试的单任务技术更有优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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