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首页> 外文期刊>Journal of Computational Methods in Sciences and Engineering >Does the linear size adjustment to estimated effort improve web applications effort estimation accuracy?
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Does the linear size adjustment to estimated effort improve web applications effort estimation accuracy?

机译：对估计工作量进行线性大小调整是否可以提高Web应用程序工作量估计的准确性？

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摘要

Over the last 16 years, and particularly over the last 8 years, Analogy-based effort estimation has been used to estimate effort for software projects and in several studies has presented comparable estimation accuracy to, or better than, algorithmic methods. The Analogy technique is also potentially easier to understand and apply by both researchers and practitioners. These two factors suggest that this technique has great potential as an effort estimation technique to be used within Companies. However, there are still several challenges, in particular regarding the type of effort adaptation to use in order to obtain the highest prediction accuracy, that need further investigation. Therefore this paper compares several methods of Analogy-based effort estimation and investigates the use of adaptation rules as a contributing factor to better estimation accuracy. Two datasets are used in the analysis; results show that the best predictions are obtained for the dataset that first, presents a continuous "cost" function, translated as a strong linear relationship between size and effort, and second, is more "intact" in terms of outliers and collinearity. Only one of the two types of adaptation rules employed generated good predictions.
机译：在过去的16年中，尤其是在过去的8年中，基于类比的工作量估算已用于估算软件项目的工作量，并且在一些研究中，其估算精度可与算法方法相媲美或优于算法方法。类比技术也可能更容易被研究人员和从业人员理解和应用。这两个因素表明，此技术作为在公司内部使用的工作量估算技术具有巨大的潜力。然而，仍然存在若干挑战，特别是关于为了获得最高的预测精度而使用的努力适应类型，需要进一步研究。因此，本文比较了几种基于类比的工作量估算方法，并研究了将自适应规则用作提高估算精度的重要因素。分析中使用了两个数据集。结果表明，对于数据集可以获得最佳预测，首先，该数据集呈现出连续的“成本”函数，转化为大小和工作量之间的强线性关系，其次，在离群值和共线性方面更“完整”。所采用的两种适应规则中只有一种产生了良好的预测。

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