Developing a real-time system requires finding a balance between the timing constraints and the functional requirements. Achieving this balance often requires last-minute, low-level intervention in the code modules -- via intensive hardware-based instrumentation and manual program optimizations. In this dissertation we present an automated, static alternative to this kind of human-intensive work. Our approach is motivated by recent advances in compiler technologies, which we extend to two specific issues on real-time programming, that is, feasibility and schedulability.

A task is infeasible if its execution time stretches over its deadline.
To eliminate such faults, we have developed a synthesis method that (1) inspects all infeasible paths, and then (2) moves instructions out of those paths to shorten the execution time.

On the other hand, schedulability of a task set denotes an ability to guarantee the deadlines of all tasks in the application. This property is affected by interactions between the tasks, as well as their individual execution times and deadlines. To address the schedulability problem, we have developed a task transformation method based on program slicing. The method decomposes a task into two subthreads: the IO-handler component that must meet the original deadline, and the state-update component that can be postponed past the deadline. This delayed-deadline approach contributes to the schedulability of the overall application. We also present a new fixed-priority preemptive scheduling strategy, which yields both a feasible priority ordering and a feasible task-slicing metric. (Also cross-referenced as UMIACS-TR-95-33)