Using influence diagrams for software risk analysis

Abstract

Influence diagrams have been used effectively in applied decision analysis to model complex systems, identify probabilistic dependence and characterize the flow of information. We argue that influence diagrams are a natural fit for decision making for software risk analysis. Our approach is very general and can be adapted for various type of software risks. We use software metrics collected at various stages of software development. The metrics data is analyzed by an influence diagram to identify the sources of errors and predict future risk items like reliability, complexity, schedule, or non-reusability.