Missing Clean Code Acceptance and Support in Practice - An Empirical Study

Paula Rachow, Sandra Schröder, Matthias Riebisch
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引用次数: 5

Abstract

Code quality is important for maintainability and sustainability of software systems, and is addressed by guidelines and peer reviews. There are well-defined methods and standards for code quality for example the Clean Code approach [1], and they are integrated with current software development process models such as SCRUM. However, developers have to be encouraged to invest effort due to the trade-off between software quality measures and projects' time pressure. Unfortunately, there are no proven hypotheses about the reasons for missing acceptance of such methods and standards by developers. To investigate hindering aspects for code quality acceptance in practice, empirical studies might help to determine the root problems and to establish solutions. However, there is a lack of empirical studies concerning this topic. Therefore, we performed an empirical study with practitioners to investigate problems and challenges while enforcing Clean Code. Semi-structured interviews were used to consult experienced practitioners from different companies and backgrounds. The transcripts were analyzed with open coding. The results showed that a lack of even one of the people-related aspects such as motivation, knowledge, experience and code quality awareness, hinders the enforcement of code quality. Surprisingly, tools might establish hindering factors due to high initial effort. As conclusions we propose implications for academic research, organization, practitioners and tool providers.
在实践中缺少干净代码的接受和支持——一项实证研究
代码质量对于软件系统的可维护性和可持续性非常重要,并且通过指导方针和同行评审来解决。对于代码质量有定义良好的方法和标准,例如Clean code方法[1],并且它们与当前的软件开发过程模型(如SCRUM)集成在一起。然而,由于软件质量度量和项目时间压力之间的权衡,必须鼓励开发人员投入精力。不幸的是,对于开发人员不接受这些方法和标准的原因,没有经过证实的假设。为了调查实践中阻碍代码质量验收的方面,实证研究可能有助于确定问题的根源并建立解决方案。然而,关于这一主题的实证研究缺乏。因此,我们与实践者一起执行了一项实证研究,在执行Clean Code时调查问题和挑战。采用半结构化访谈,咨询来自不同公司和背景的经验丰富的从业人员。转录本采用开放编码分析。结果表明,缺乏哪怕一个与人相关的方面,如动机、知识、经验和代码质量意识,都会阻碍代码质量的实施。令人惊讶的是,由于高初始努力,工具可能会建立阻碍因素。作为结论,我们提出了对学术研究、组织、从业者和工具提供者的启示。
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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