Selecting Best Practices for Effort Estimation

@article{Menzies2006SelectingBP,
  title={Selecting Best Practices for Effort Estimation},
  author={Tim Menzies and Zhihao Chen and Jairus Hihn and Karen T. Lum},
  journal={IEEE Transactions on Software Engineering},
  year={2006},
  volume={32}
}
Effort estimation often requires generalizing from a small number of historical projects. Generalization from such limited experience is an inherently underconstrained problem. Hence, the learned effort models can exhibit large deviations that prevent standard statistical methods (e.g., t-tests) from distinguishing the performance of alternative effort-estimation methods. The COSEEKMO effort-modeling workbench applies a set of heuristic rejection rules to comparatively assess results from… CONTINUE READING

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