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Precise Input-Data Dependency Analysis for Hard Real-Time Systems
In a growing number of hard real-time systems, static analysis techniques are used to bound the worst case execution time (WCET) of the system's tasks. In order to successfully predict the temporal properties of larger systems with less effort, we investigate the relation between input data and control flow decisions. In this talk, we present our approach to a precise input-data dependency analysis, and discuss possible applications. The analysis allows us to determine the influence of input parameters on flow facts, or speed up loop bound analyses, for example. Furthermore, the notion of input data independence is used to define software policies restricting the influence of input data on flow facts, facilitating the systematic construction of analyzable systems. The ongoing implementation work is conducted using LLVM, a modern compiler framework which both provides a rich analysis infrastructure, and allows us to test the approach against real world code at low cost.