Software Quality Assessment and Project Risk Management Based on Bayesian Belief Networks

The ability to reliably predict the risk for a software project presents a significant advantage for a development team. It provides an opportunity to address high risk components earlier in the development life cycle, when their impact is minimized. This article proposes a Bayesian Belief Networks (BBNs) model that captures the evolution of the quality of a software product and provides reliable forecasts of the end quality of the software being developed in light of factors that affect project risk. Insights into risk management, development team skill, software process maturity, and software problem complexity are hypothesized as driving factors of software product quality. The cause-effect relationships between these factors and the elements of software quality and risk management techniques are modeled using BBNs. The BBN software project risk assessment model is utilized to quantify the factors that influence and represent software quality.