Does the linear size adjustment to estimated effort improve web applications effort estimation accuracy?

Abstract

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.