Analyzing Uncertainty in Release Planning: A Method and Experiment for Fixed-Date Release Cycles

Release planning—deciding what features to implement in upcoming releases of a software system—is critical activity iterative development. Many release planning methods exist, but most ignore the inevitable uncertainty estimating development effort and business value. The article’s objective is study whether analyzing during generates better plans than if ignored. To this question, we have developed novel method under uncertainty, called BEARS, that models using Bayesian probability distributions recommends maximize expected net present value punctuality. We then compare recommended by BEARS those on 32 problems. experiment shows with higher punctuality thereby indicating harmful effects ignoring planning. These results highlight importance eliciting estimations call for increased research these areas.