Large Scale What-if Queries: A Case 
Study Using COCOMO-II






simulations, effort estimation, risk assessment, COCOMO-II


When a lack of data inhibits 
decision making, large scale what-if queries can 
be conducted over the uncertain parameter ranges. 
Such what-if queries can generate an overwhelming 
amount of data. In the case study 
explored here, machine learning was used to 
summarize the output of a Monte Carlo 
simulation of the COCOMO-II software effort estimation 
model. Based on that summary, key risk 
reduction factors were identified. This method of 
understanding models is general to many application 
areas.