Building Software Cost Estimation Models using Homogenous Data

Several studies have been conducted to determine if company-specific cost models deliver better prediction accuracy than cross-company cost models. However, mixed results have left the question still open for further investigation. We suspect this to be a consequence of heterogenous data used to build cross-company cost models. In this paper, we build cross-company cost models using homogenous data by grouping projects by their business sector. Our results suggest that it is worth to train models using only homogenous data rather than all projects available.