Measuring the Heterogeneity of Crosscompany Datasets

Loading...
Thumbnail Image

View/Download File

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Measuring the Heterogeneity of Crosscompany Datasets

Published Date

2010

Publisher

Type

Report

Abstract

As a standard practice, general effort estimate models are calibrated from large cross-company datasets. However, many of the records within such datasets are taken from companies that have calibrated the model to match their own local practices. Locally calibrated models are a double-edged sword; they often improve estimate accuracy for that particular organization, but they also encourage the growth of local biases. Such biases remain present when projects from that firm are used in a new cross-company dataset. Over time, such biases compound, and the reliability and accuracy of a general model derived from the data will be affected by the increased level of heterogeneity. In this paper, we propose a statistical measure of the exact level of heterogeneity of a cross-company dataset. In experimental tests, we measure the heterogeneity of two COCOMO-based datasets and demonstrate that one is more homogeneous than the other. Such a measure has potentially important implications for both model maintainers and model users. Furthermore, a heterogeneity measure can be used to inform users of the appropriate data handling techniques.

Keywords

Description

Associated research group: Critical Systems Research Group

Related to

Replaces

License

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

PROFES 2010

Other identifiers

Suggested citation

Chen, Jia; Yang, Ye; Zhang, Wen; Gay, Gregory. (2010). Measuring the Heterogeneity of Crosscompany Datasets. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/217411.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.