Towards a framework to support large scale sampling in software engineering surveys

R. Mello, Pedro Correa da Silva, P. Runeson, G. Travassos
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引用次数: 17

Abstract

Context: The low quality and small size of samples in empirical studies in software engineering hamper the interpretation and generalization of their results. Therefore, enlarging sample sizes and improving their quality represent an important research challenge. Goal: We aim to define a conceptual framework, including requirements for establishing adequate sources for sampling subjects in software engineering surveys. Method: We use previous experience on applying systematic sampling strategies combined with contemporary web technologies in previously executed surveys, to organize the conceptual framework. We analyze its application to different sources of sampling. Results: The framework was observed to be feasible after its application to nine different large-scale sources of sampling. Conclusions: The analyzed crowdsourcing tools do not support essential requirements to be considered sources of sampling, while free-lancing tools and professional social network do.
建立一个支持软件工程调查中大规模抽样的框架
背景:在软件工程的实证研究中,低质量和小尺寸的样本阻碍了他们的结果的解释和推广。因此,扩大样本数量和提高样本质量是一个重要的研究挑战。目标:我们的目标是定义一个概念性框架,包括在软件工程调查中为抽样主题建立足够的资源的需求。方法:我们利用以前在以前执行的调查中应用系统抽样策略结合当代网络技术的经验来组织概念框架。我们分析了它在不同采样源中的应用。结果:将该框架应用于9个不同的大规模抽样来源后,发现该框架是可行的。结论:所分析的众包工具不支持被视为抽样来源的基本要求,而自由职业者工具和专业社交网络则支持。
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