重访基于早期开发活动的软件开发工作量评估

Masateru Tsunoda, Koji Toda, Kyohei Fushida, Yasutaka Kamei, M. Nagappan, Naoyasu Ubayashi
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引用次数: 10

摘要

许多关于软件评估的研究项目使用软件大小作为主要的解释变量。然而,从业者有时会使用早期阶段活动(如计划和需求分析)的工作量与软件整个开发阶段的工作量的比率,以便估计工作量。在本文中,我们主要关注基于早期阶段活动的工作量估算。该研究的目标是检查早期阶段工作和软件规模与软件开发工作之间的关系。为了实现这个目标,我们使用早期阶段的工作量作为解释变量来构建工作量估计模型,并将这些模型的估计精度与基于软件大小的工作量估计模型进行比较。此外,我们使用早期阶段的工作和软件规模构建了评估模型。在我们的实验中,我们使用了从软件开发公司收集的ISBSG数据集,并将计划阶段的工作和需求分析工作视为早期阶段的工作。实验结果表明,当软件大小和计划和需求分析阶段工作量的总和被用作解释变量时,估计精度得到了最大的提高(平均平衡相对误差从148.4%提高到75.4%)。基于结果,我们建议将早期阶段的工作和软件大小都用作解释变量,因为这种组合显示了较高的准确性,并且没有多重共线性问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Revisiting software development effort estimation based on early phase development activities
Many research projects on software estimation use software size as a major explanatory variable. However, practitioners sometimes use the ratio of effort for early phase activities such as planning and requirement analysis, to the effort for the whole development phase of the software in order to estimate effort. In this paper, we focus on effort estimation based on the effort for early phase activities. The goal of the research is to examine the relationship of early phase effort and software size with software development effort. To achieve the goal, we built effort estimation models using early phase effort as an explanatory variable, and compared the estimation accuracies of these models to the effort estimation models based on software size. In addition, we built estimation models using both early phase effort and software size. In our experiment, we used ISBSG dataset, which was collected from software development companies, and regarded planning phase effort and requirement analysis effort as early phase effort. The result of the experiment showed that when both software size and sum of planning and requirement analysis phase effort were used as explanatory variables, the estimation accuracy was most improved (Average Balanced Relative Error was improved to 75.4% from 148.4%). Based on the result, we recommend that both early phase effort and software size be used as explanatory variables, because that combination showed the high accuracy, and did not have multicollinearity issues.
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