A model and sensitivity analysis of the quality economics of defect-detection techniques

TL;DR

This paper introduces an analytical stochastic model to analyze the economics of defect detection techniques in software development, highlighting key factors influencing costs and revenues.

Contribution

It presents a novel model that incorporates both dynamic and static defect detection techniques and applies sensitivity analysis to identify critical economic factors.

Findings

Key factors influencing defect detection costs identified

Model helps prioritize research and measurement efforts

Sensitivity analysis guides model simplification

Abstract

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.