Reducing biases in individual software effort estimations: a combining approach

Authors:
Qi Li;Qing Wang;Ye Yang;Mingshu Li
Affiliations:
Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China
Venue:
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Year:
2008

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Abstract

Software effort estimation techniques abound, each with its own set of advantages and disadvantages, and no one proves to be the single best answer. Combining estimating is an appealing approach. Avoiding the difficult problem of choosing the single "best" technique, it solves the problem by asking which techniques would help to improve accuracy, assuming that each has something to contribute. In this paper, we firstly introduce the systematic "external" combining idea into the field of software effort estimation, and estimate software effort using Optimal Linear Combining (OLC) method with an experimental study based on a real-life data set. The result indicates that combining different techniques can significantly improve the accuracy and consistency of software effort estimation by making full use of information provided by all components, even the much "worse" one.