LAUSR

Modern embedded software includes complex functionalities and routines, often implemented by splitting the code across different tasks. Such tasks communicate their partial computations to their successors, forming a task chain. Traditionally, this architecture relies on the assumption of hard deadlines and timely communication. However, in actual implementations, tasks may miss their deadlines, thus affecting the propagation of their data. This article analyzes a task chain in which tasks can fail to complete their jobs according to the weakly-hard task model. We explore how missing deadlines affect chains in terms of classic latency metrics and valid data paths. Our analysis, based on mixed integer linear programming, extracts the worst-case deadline miss pattern for any given performance metric.