Applying moving windows to software effort estimation

Models for estimating software development effort are commonly built and evaluated using a set of historical projects. An important question is which projects to use as training data to build the model: should it be all of them, or a subset that seems particularly relevant? One factor to consider is project age: is it best to use the entire history of past projects, or is it more appropriate in a rapidly changing world to use a window of recent projects? We investigate the effect on estimation accuracy of using a moving window, using projects from the ISBSG data set. We find that using a moving window can improve accuracy, and we make some observations about factors that influence the range of possible window sizes and the best window size.