设计团队的质量是影响软件工作量评估的因素

S.I.K. Wu
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引用次数: 7

摘要

在过去的十几年中,学术界和实践者在软件开发生命周期的早期阶段提出了各种各样的工作模型。一些人指出可以使用代码行(LOC)和COCOMO来预测工作,另一些人强调可以使用功能点分析(FPA)或其他方法来进行预测。该研究试图开发一个模型,通过研究和分析中小型应用软件来评估软件的工作量。为了开发这样一个模型,从一家软件公司收集了50个已完成的软件项目。利用样本数据,识别并提取设计团队因素。将其应用于简单的回归分析,构建了一个准确率为MMRE=9%的工作量估算预测软件。研究结果带来了几个好处。首先,由于在识别这些因素时使用了简单的过程,估计问题被最小化。其次,预测的软件项目仅局限于特定的环境,而不是基于行业环境。我们相信工作量估算的准确性可以得到提高。分析结果表明,基于软件开发生命周期早期提取的数据,可以建立简单实用的预测模型。我们希望这个模型能在不久的将来为项目设计者规划和控制软件项目提供有价值的想法和建议
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The quality of design team factors on software effort estimation
Over the past ten couple of years, there is a variety of effort models proposed by academicians and practitioners at early stage of software development life cycle. Some addressed that efforts could be predicted using lines of codes (LOC) and COCOMO, others emphasized that it could be made using function point analysis (FPA) or others. The study seeks to develop a model that estimates software effort by studying and analyzing small and medium scale application software. To develop such a model, 50 completed software projects are collected from a software company. With the sample data, design team factors are identified and extracted. By applying them to simple regression analyses, a prediction of software of effort estimates with accuracy of MMRE=9% was constructed. The results give several benefits. First, the estimation problems are minimized due to the simple procedure used in identifying those factors. Second, the predicted software projects are only limited to a specific environment rather than being based upon industry environment. We believe the accuracy of effort estimates can be improved. According to the results analyzed, the work shows that it is possible to build up simple and useful prediction model based on data extracted at the early stage of software development life cycle. We hope this model can provide valuable ideas and suggestions for project designers for planning and controlling software projects in near future
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