@article{16998,
  author = {Magne J{\o}rgensen},
  title = {Improved Measurement of Software Development Effort Estimation Bias},
  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.},
  year = {2023},
  journal = {Information and software technology},
  volume = {157},
  pages = {107157},
  publisher = {Elsevier},
}