Evaluating Quality of Primary Studies on Determining Object-Oriented Code Refactoring Candidates

Jehad Al Dallal
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引用次数: 3

Abstract

Refactoring is a maintenance task that aims at improving the quality of a software source code by restructuring it without altering its external behavior. Identifying refactoring opportunities by manually inspecting and analyzing the source code of the system under consideration is a time consuming and costly process. Researchers, in this area, typically introduce fully or semi-automated techniques to determine or predict refactoring candidates and they report related evaluation studies. The quality of the performed studies has a great impact on the accuracy of the obtained results. In this paper, we demonstrate an application for a proposed framework that evaluates published primary studies (PSs) on refactoring prediction/identification techniques. The framework is applied on 47 selected PSs to evaluate the quality of the studies based on their design, conduct, analysis, and conclusion. We used the results to comment on the weaknesses of the existing PSs and the issues that have to be considered with more attention in future studies.
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评估确定面向对象代码重构候选者的初步研究的质量
重构是一项维护任务,旨在通过在不改变外部行为的情况下重构软件源代码,从而提高软件源代码的质量。通过手工检查和分析所考虑的系统的源代码来确定重构机会是一个耗时且昂贵的过程。在这个领域,研究人员通常会引入完全或半自动化的技术来确定或预测重构候选,并报告相关的评估研究。所进行研究的质量对所得结果的准确性有很大的影响。在本文中,我们演示了一个拟议框架的应用程序,该框架评估了有关重构预测/识别技术的已发表的初步研究(ps)。该框架应用于47个选定的PSs,以评估基于其设计,实施,分析和结论的研究质量。我们使用这些结果来评论现有ps的弱点以及在未来的研究中需要更多关注的问题。
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