  The rise of transient faults in modern hardware requires system designers to
consider errors occurring at runtime. Both hardware- and software-based error
handling must be deployed to meet application reliability requirements. The
level of required reliability can vary for system components and depend on
input and state, so that a selective use of resilience methods is advised,
especially for resource-constrained platforms as found in embedded systems. If
an error occurring at runtime can be classified as having negligible or
tolerable impact, less effort can be spent on correcting it. As the actual
impact of an error is often dependent on the state of a system at time of
occurrence, it can not be determined precisely for highly dynamic workloads in
data-driven applications. We present a concept to estimate error propagation in
sets of tasks with variable data dependencies. This allows for a coarse grained
analysis of the impact a failed task may have on the overall output. As an
application example, we demonstrate our method for a typical dynamic embedded
application, namely a decoder for the H.264 video format.
