Smells in software test code: A survey of knowledge in industry and academia
Smells in software test code: A survey of knowledge in industry and academia
复制标题
DOI：
10.1016/j.jss.2017.12.013
复制
发表时间：
2018-04-01
影响因子：
3.5
通讯作者：
Kucuk, Baris
中科院分区：
文献类型：
--
作者：
Garousi, Vahid;Kucuk, Baris
作为一种反图案，测试气味被定义为设计较差的测试，其存在可能会对测试套件和生产代码的质量产生负面影响。测试气味是从业人员和研究人员之间进行积极讨论的主题，并且不断提供各种应对气味的准则，以预防气味，气味检测和气味纠正。由于在该领域有庞大的灰色文献以及大量的研究，因此从业者和研究人员可以找到和综合如此大的文献是不切实际的。由上述需求的激励，并找出我们作为社区中对测试代码中的气味的了解，我们对科学文献和从业者的灰色文献进行了“多局部”文献映射（分类）。通过对行业（120个来源）和学术界（46个来源）的测试气味的所有来源进行调查，总共166个来源，我们的评论介绍了测试气味的最大目录，以及指南/技术的摘要以及用于处理的工具那些气味。本文旨在通过作为对这一重要领域的广阔知识的“索引”，并帮助他们开发高质量的测试脚本，并最大程度地减少测试气味及其其最小化，从而使读者（从业人员和研究人员）受益。大型测试自动化项目的负面后果。 （c）2017 Elsevier Inc.保留所有权利。
As a type of anti-pattern, test smells are defined as poorly designed tests and their presence may negatively affect the quality of test suites and production code. Test smells are the subject of active discussions among practitioners and researchers, and various guidelines to handle smells are constantly offered for smell prevention, smell detection, and smell correction. Since there is a vast grey literature as well as a large body of research studies in this domain, it is not practical for practitioners and researchers to locate and synthesize such a large literature. Motivated by the above need and to find out what we, as the community, know about smells in test code, we conducted a 'multivocal' literature mapping (classification) on both the scientific literature and also practitioners' grey literature. By surveying all the sources on test smells in both industry (120 sources) and academia (46 sources), 166 sources in total, our review presents the largest catalogue of test smells, along with the summary of guidelines/techniques and the tools to deal with those smells. This article aims to benefit the readers (both practitioners and researchers) by serving as an "index" to the vast body of knowledge in this important area, and by helping them develop high-quality test scripts, and minimize occurrences of test smells and their negative consequences in large test automation projects. (C) 2017 Elsevier Inc. All rights reserved.