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Evaluating Pred(p) and standardized accuracy criteria in software development effort estimation

机译:在软件开发工作量评估中评估Pred(p)和标准化准确性标准

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Software development effort estimation (SDEE) plays a primary role in software project management. But choosing the appropriate SDEE technique remains elusive for many project managers and researchers. Moreover, the choice of a reliable estimation accuracy measure is crucial because SDEE techniques behave differently given different accuracy measures. The most widely used accuracy measures in SDEE are those based on magnitude of relative error (MRE) such as mean/median MRE (MMRE/MedMRE) and prediction at level p (Pred(p)), which counts the number of observations where an SDEE technique gave MREs lower than p. However, MRE has proven to be an unreliable accuracy measure, favoring SDEE techniques that underestimate. Consequently, an unbiased measure called standardized accuracy (SA) has been proposed. This paper deals with the Pred(p) and SA measures. We investigate (1) the consistency of Pred(p) and SA as accuracy measures and SDEE technique selectors, and (2) the relationship between Pred(p) and SA. The results suggest that Pred(p) is less biased towards underestimates and generally selects the same best technique as SA. Moreover, SA and Pred(p) measure different aspects of technique performance, and SA may be used as a predictor of Pred(p) by means of the 3 association rules.
机译:软件开发工作量估算(SDEE)在软件项目管理中起主要作用。但是,对于许多项目经理和研究人员而言,选择合适的SDEE技术仍然遥不可及。此外,选择可靠的估计精度指标至关重要,因为SDEE技术在不同的精度指标下表现会有所不同。 SDEE中使用最广泛的准确性度量是基于相对误差(MRE)的幅度的度量,例如均值/中值MRE(MMRE / MedMRE)和p级的预测(Pred(p)),它计算观察值SDEE技术使MRE低于p。但是,MRE已被证明是一种不可靠的准确度测量方法,它支持被低估的SDEE技术。因此,提出了一种称为标准精度(SA)的无偏措施。本文讨论了Pred(p)和SA措施。我们研究(1)作为精度度量和SDEE技术选择器的Pred(p)和SA的一致性,以及(2)Pred(p)和SA之间的关系。结果表明,Pred(p)偏向于低估的程度较小,并且通常选择与SA相同的最佳技术。此外,SA和Pred(p)衡量技术性能的不同方面,并且SA可以通过3个关联规则用作Pred(p)的预测指标。

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