Calibrating Productivity Drivers for Software Customisation Projects

Effort estimation for software customisation projects is a challenging task. Similar to the COCOMO approach, an initial estimate can be based on basic project characteristics, and then modified according to various productivity drivers. The aim of this paper is to build on an initial estimation model, generated from a set of contributing factors for software customisation projects, and to improve the accuracy of the model through calibration of effort multipliers derived from customisation project characteristics. Projects from Release 12 of the ISBSG Data Repository were analysed to see which of the productivity drivers were usefully related to variations in software productivity, after other project characteristics had been taken into account. The effect on estimation accuracy of multiplying an initial estimate by each of these productivity drivers was evaluated, in terms of changes in mean and median absolute error, and mean and median magnitude of relative error. Finally, a set of useful productivity drivers is identified for customisation projects, and their effect is quantified. They are found to improve effort estimation accuracy significantly.