Authors | M. Jørgensen |
Title | Improved Measurement of Software Development Effort Estimation Bias |
Afilliation | Software Engineering |
Project(s) | EDOS: Effective Digitalization of Public Sector |
Status | Published |
Publication Type | Journal Article |
Year of Publication | 2023 |
Journal | Information and software technology |
Publisher | Elsevier |
Abstract | Context: While prior software development effort estimation research has examined the properties of estimation error measures, there has not been much research on the properties of measures of estimation bias. Objectives: Improved measurement of software development effort estimation bias. Methods: Analysis of the extent to which measures of estimation bias meet the criterion that perfect estimates should result in zero bias. Results: Recommendations for measurement of estimation bias for estimates of the mean, median, and mode software development effort. The results include the recommendation to avoid a commonly used measure of effort estimation bias. Conclusion: Proper evaluation of estimation bias requires knowledge about the type of estimates evaluated, together with the selection of a measure of estimation bias that gives zero bias for perfect estimates of that type. |
Citation Key | 43106 |