  One of the main cost factors in software development is the detection and
removal of defects. However, the relationships and influencing factors of the
costs and revenues of defect-detection techniques are still not well
understood. This paper proposes an analytical, stochastic model of the
economics of defect detection and removal to improve this understanding. The
model is able to incorporate dynamic as well as static techniques in contrast
to most other models of that kind. We especially analyse the model with
state-ofthe-art sensitivity analysis methods to (1) identify the most relevant
factors for model simplification and (2) prioritise the factors to guide
further research and measurements.
