Slicing Real-Time Programs for Enhanced Schedulability

Abstract

In this article we present a compiler-based technique to help develop correct real-time systems. The domain we consider is that of multiprogrammed real-time applications, in which periodic tasks control physical systems via interacting with external sensors and actuators. While a system is up and running, these operations must be performed as specified - otherwise the system may fail. Correctness depends not only on each program individually, but also on the time-multiplexed behavior of all of the programs running together. Errors due to overloaded resources are exposed very late in a development process, and often at runtime. They are usually remedied by human-intensive activities such as instrumentation, measurement, code tuning and redesign. We describe a static alternative to this process, which relies on well-accepted technologies from optimizing compilers and fixed-priority scheduling. Specifically, when a set of tasks are found to be overloaded, a scheduling analyzer determines candidate tasks to be transformed via program slicing. The slicing engine decomposes each of the selected tasks into two fragments: one that is "time critical" and the other "unobservable." The unobservable part is then spliced to the end of the time-critical code, with the external semantics being maintained. The benefit is that the scheduler may postpone the unobservable code beyond its original deadline, which can enhance overall schedulability. While the optimization is completely local, the improvement is realized globally, for the entire task set.