Do adaptation rules improve web cost estimation?

Abstract

Analogy-based estimation has, over the last 15 years, and particularly over the last 7 years, emerged as a promising approach with comparable accuracy to, or better than, algorithmic methods in some studies. In addition, it is potentially easier to understand and apply; these two important factors can contribute to the successful adoption of estimation methods within Web development companies. We believe therefore, analogy-based estimation should be examined further.This paper compares several methods of analogy-based effort estimation. In particular, it 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 "unspoiled" in terms of outliers and collinearity. Only one of the two types of adaptation rules employed generated good predictions.