  In recent years, there has been considerable effort to modernize existing and
new nuclear power plants with digital instrumentation and control systems.
However, there has also been considerable concern both by industry and
regulatory bodies for the risk and consequence analysis of these systems. Of
concern are digital common cause failures specifically due to software defects.
These failures by the software can occur in both the control and monitoring of
a system. While many methods have been proposed to identify software failure
modes, such as Systems Theoretic Process Analysis, Hazard and Consequence
Analysis for Digital Systems, etc., these methods are focused primarily on the
control action pathway of a system. In contrast, the information feedback
pathway lacks Unsafe Control Actions, which are typically related to software
basic events; thus, assessment of software basic events in such systems is
unclear. In this work, we present the idea of intermediate processors and
Unsafe Information Flow (UIF) to help safety analysts trace failure mechanisms
in the feedback pathway and how they can be integrated into a fault tree for
improved assessment capability. The concepts presented are demonstrated in two
comprehensive case studies, a smart sensor integrated platform for unmanned
autonomous vehicles and another on a representative advanced human system
interface for safety critical plant monitoring. The qualitative software basic
events are identified, and a fault tree analysis is conducted based on a
modified Redundancy guided Systems theoretic Hazard Analysis methodology. The
case studies demonstrate the use of UIFs and intermediate processors in the
fault tree to improve traceability of software failures in highly complex
digital instrumentation feedback. The improved method clarifies fault tree
construction when multiple component dependencies are present in the system.
