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arXiv 2002.07764cs.SE
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软件工程研究中的抽样:评论与指南

Sampling in Software Engineering Research: A Critical Review and Guidelines

Sebastian Baltes, Paul Ralph

摘要:

在经验性的软件工程研究中,代表性抽样显得很少见。并不是所有的研究都需要有代表性的样本,但是普遍缺乏代表性的样本会破坏一个科学领域。因此,本文报告了一个重要的审查抽样状态,在最近的高质量的软件工程研究。主要发现如下:(1)随机抽样很少;(2)复杂的抽样策略非常罕见;(3)抽样、代表性和随机性往往被误解。这些发现表明,软件工程研究有一个普遍性危机。为了解决这些问题,本文综合了现有的知识抽样到一个简洁的底漆,并提出了广泛的指导方针,以提高行为,演示和评估抽样在软件工程研究。它进一步建议,虽然研究人员应该争取更有代表性的样本,非概率抽样通常是反复无常的,特别是误导为主的定性研究。

英文摘要:

Representative sampling appears rare in empirical software engineering research. Not all studies need representative samples, but a general lack of representative sampling undermines a scientific field. This article therefore reports a critical review of the state of sampling in recent, high-quality software engineering research. The key findings are: (1) random sampling is rare; (2) sophisticated sampling strategies are very rare; (3) sampling, representativeness and randomness often appear misunderstood. These findings suggest that software engineering research has a generalizability crisis. To address these problems, this paper synthesizes existing knowledge of sampling into a succinct primer and proposes extensive guidelines for improving the conduct, presentation and evaluation of sampling in software engineering research. It is further recommended that while researchers should strive for more representative samples, disparaging non-probability sampling is generally capricious and particularly misguided for predominately qualitative research.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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