Use of Bayesian Belief Networks when combining disparate sources of information in the safety assessment of software-based systems

The paper discusses how disparate sources of information can be combined in the safety assessment of software-based systems. The emphasis is put on an emerging methodology, relevant for intelligent product-support systems, to combine information about disparate evidences systematically based on Bayesian Belief Networks. The objective is to show the link between basic information and the confidence one can have in a system. How one combines the Bayesian Belief Net (BBN) method with a software safety standard (RTCA/DO-178B) for safety assessment of software-based systems is also discussed. Finally, the applicability of the BBN methodology and experiences from cooperative research work together with Kongsberg Defence & Aerospace and Det Norske Veritas, and ongoing research with VTT Automation are presented.