An empirical study using task assignment patterns to improve the accuracy of software effort estimation

In most software development organizations, there is seldom a one-to-one mapping between software developers and development tasks. It is frequently necessary to concurrently assign individuals to multiple tasks and to assign more than one individual to work cooperatively on a single task. A principal goal in making such assignments should be to minimize the effort required to complete each task. But what impact does the manner in which developers are assigned to tasks have on the effort requirements? This paper identifies four task assignment factors: team size, concurrency, intensity, and fragmentation. These four factors are shown to improve the predictive ability of the well-known Intermediate COCOMO cost estimation model. A parsimonious effort estimation model is also derived that utilizes a subset of the task assignment factors and Unadjusted Function Points. For the data examined, this parsimonious model is shown to have goodness of fit and quality of estimation superior to that of the COCOMO model, while utilizing fewer cost factors.