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Mining Plausible Hypotheses from the Literature Via Meta-Analysis

机译:通过荟萃分析从文献中挖掘合理的假设

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摘要

Meta-analysis is highly advocated in many fields of empirical research such as medicine and psychology, due to its capability to synthesize quantitative evidence of effects from the literature, based on statistical analysis. However, the adoption of meta-analysis to software engineering is still suffering from inertia, despite the fact that many software engineering researchers have long been arguing the need for it. As an attempt to move beyond the lockstep, we in this paper explore a different use of meta-analysis. Our proposition is that meta-analysis is useful for mining hypotheses because their plausibility is backed by evidence accumulated in the literature, and thus researchers could focus their effort on the areas that are of particular need. We assess our proposition by conducting a lightweight case study on the literature of defect prediction. We found that three out of five hypotheses we extract from our meta-analysis were indeed investigated in separate papers, indicating the usefulness of our approach. We also recognize two uninvestigated hypotheses whose validity we plan to investigate in the future.
机译:元分析在医学和心理学等许多实证研究领域都得到了大力提倡,因为它具有根据统计分析从文献中综合量化影响证据的能力。但是,尽管许多软件工程研究人员长期以来一直在争论对元分析的需求,但在软件工程中仍然采用元分析。为了超越锁定的步伐,我们在本文中探索了元分析的另一种用法。我们的主张是,荟萃分析可用于挖掘假设,因为其合理性得到了文献中积累的证据的支持,因此研究人员可以将精力集中在特别需要的领域。我们通过对缺陷预测文献进行轻量级案例研究来评估我们的建议。我们发现,我们从荟萃分析中提取的五分之三的假设确实在单独的论文中进行了研究,表明该方法的有用性。我们还认识到两个未调查的假设,我们计划在将来对其进行研究。

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