EXAMINING THE FEASIBILITY OF A CASE-BASED REASONING MODEL FOR SOFTWARE EFFORT ESTIMATION

Existing algorithmic models fail to produce accurate software development effort estimates. To address this problem, a case-based reasoning model, called Estor, was developed based on the verbal protocols of a human expert solving a set of estimation problems. Estor was then presented with 15 software effort estimation tasks. The estimates of Estor were compared to those of the expert as well as those of the function point and COCOMO estimations of the projects. The estimates generated by the human expert and Estor were more accurate and consistent than those of the function point and COCOMO methods. In fact, Estor was nearly as accurate and consistent as the expert. These results suggest that a case-based reasoning approach for software effort estimation holds promise and merits additional research.