COBRA: a hybrid method for software cost estimation, benchmarking, and risk assessment

Current cost estimation techniques have a number of drawbacks. For example, developing algorithmic models requires extensive past project data. Also, off-the-shelf models have been found to be difficult to calibrate but inaccurate without calibration. Informal approaches based on experienced estimators depend on estimators' availability and are not easily repeatable, as well as not being much more accurate than algorithmic techniques. We present a method for cost estimation that combines aspects of algorithmic and experiential approaches (referred to as COBRA, COst estimation, Benchmarking, and Risk Assessment). We find through a case study that cost estimates using COBRA show an average ARE of 0.09. Although we do not have the room to describe the benchmarking and risk assessment parts, the reader will find detailed information in (Briand et al., 1997).