What do we know about perspective-based reading? An approach for quantitative aggregation in software engineering

M. Ciolkowski
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引用次数: 45

Abstract

One of the main challenges in empirical software engineering today lies in the aggregation of evidence. Existing summaries often use qualitative narrative approaches or ad-hoc quantitative methods, such as box plots. With these, information important for decision makers, such as existence and magnitude of a technology's effect, is hard to obtain objectively. Meta-analysis addresses this issue by providing objective quantitative information about a set of studies; however, its usefulness for software engineering studies suffers from high heterogeneity of the studies and missing information. In this paper, we describe an approach for quantitative aggregation of controlled experiments that reduces these two problems. We demonstrate the approach by aggregating available experiments to investigate whether Perspective-Based reading (PBR) improves team effectiveness compared to alternative reading approaches. We then compare the results of our aggregation to previous summaries addressing PBR's team effectiveness. Although the findings are similar, our approach is able to provide the required quantitative information objectively. Our aggregation showed that there is no clear positive effect of PBR: Inspection teams using PBR on requirements documents are more effective when compared to ad-hoc approaches, but are less effective when compared to checklists. In addition, we found strong indicators of researcher bias.
我们对基于视角的阅读了解多少?软件工程中的一种定量聚合方法
当今经验软件工程的主要挑战之一在于证据的聚合。现有的摘要通常使用定性叙述方法或特定的定量方法,如箱形图。在这种情况下,很难客观地获得对决策者重要的信息,例如技术影响的存在和程度。荟萃分析通过提供一系列研究的客观定量信息来解决这个问题;然而,它对软件工程研究的有用性受到研究的高度异质性和信息缺失的影响。在本文中,我们描述了一种减少这两个问题的控制实验的定量聚合方法。我们通过汇总现有的实验来验证基于视角的阅读(PBR)与其他阅读方法相比是否能提高团队效率。然后,我们将聚合的结果与先前处理PBR团队效率的摘要进行比较。虽然研究结果相似,但我们的方法能够客观地提供所需的定量信息。我们的汇总显示了PBR没有明显的积极影响:在需求文档上使用PBR的检查团队与特定的方法相比更有效,但是与检查清单相比效率更低。此外,我们还发现了研究人员偏见的强烈指标。
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