A Study of the Effect of Data Normalization on Software and Information Quality Assessment
A Study of the Effect of Data Normalization on Software and Information Quality Assessment
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数据标准化对软件和信息质量评估的影响研究
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Anna Wingkvist
中科院分区：
文献类型：
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作者：
Morgan Ericsson;Welf Löwe;Tobias Olsson;Daniel Toll;Anna Wingkvist
质量模型中的间接指标定义了直接指标的加权集成，以提供更高级别的质量指标。本文提出了一项案例研究，该案例研究质量质量模型在多大程度上取决于有关直接指标值分布的统计假设。我们改变了三家公司质量评估工作所使用的归一化，同时保持质量模型，指标，指标实施，从而使指标值持续不变。我们发现归一化对工件的排名（例如类别）具有相当大的影响。我们还研究了归一化如何影响质量趋势，并发现正常化对质量趋势有很大影响。基于这些发现，我们发现像今天一样，继续在质量模型中汇总不同的指标是值得怀疑的。
Indirect metrics in quality models define weighted integrations of direct metrics to provide higher-level quality indicators. This paper presents a case study that investigates to what degree quality models depend on statistical assumptions about the distribution of direct metrics values when these are integrated and aggregated. We vary the normalization used by the quality assessment efforts of three companies, while keeping quality models, metrics, metrics implementation and, hence, metrics values constant. We find that normalization has a considerable impact on the ranking of an artifact (such as a class). We also investigate how normalization affects the quality trend and find that normalizations have a considerable effect on quality trends. Based on these findings, we find it questionable to continue to aggregate different metrics in a quality model as we do today.