Economies and diseconomies of scale in software engineering

A software development manager will often need to make decisions about the allocation of resources across a number of different development projects. These projects may vary in size, in importance, and in the potential value to the organisation of the software that is to be produced. Based upon these and other considerations, a manager might consider an increase in the resource allocation for a particular project. They might also consider changing the size of a planned software release by including or excluding a number of features. In doing this, the manager will need to consider economies, or diseconomies, of scale: if a project is given twice the resources, will the software be delivered in half the time? Will a particular project remain on schedule, despite a headcount reduction of 50%, if the size of the next deliverable is reduced also by 50%? If a software product would earn the company a certaiD amount if delivered in one month, and a lesser amount if delivered after that time, how much resource should be allocated to its development? Existing effort prediction models provide some guidance, but fail to agree about the extent, or even the existence, of economies and diseconomies of scale. The models are also limited to effort and scheduling predictions for a single project; there is no provision for the optimization of resource allocation, release sizing, and release scheduling across a portfolio of projects. This dissertation uses a new prediction model, derived from a large database of empirical results, to show the existence of an economy of scale with respect to project size, and a diseconomy of scale with respect to team size. It uses this model as a basis for the comparison and validation of the two leading prediction models, and shows that a failure to address the diseconomy of scale to team size can lead to significant errors. Drawing upon the tools and techniques of financial portfolio management, the model is used as the basis of an "economic framework" for software development optimization, a set of tools for optimizing resource allocation and release sizing across a portfolio of projects, in terms of the net value obtained from the software produced. This framework is extended to address declining marginal value and to provide an indication of risk and variability across a project portfolio.EThOS - Electronic Theses Online ServiceGBUnited Kingdo